Home » Darwinism » Uncommon Descent Contest Question 10: Provide the Code for Dawkins’ WEASEL Program

Uncommon Descent Contest Question 10: Provide the Code for Dawkins’ WEASEL Program

Special invitation for Richard Dawkins – but any civil person is entitled to enter.

There’s been some discussion here and elsewhere whether the the recent IEEE article by Dembski and Marks correctly characterizes Richard Dawkins’ famous METHINKS IT IS LIKE A WEASEL program.

Does the program ratchet correct letters or does it let them vary? One is a partitioned or stair-step search, the other a more realistic evolutionary search. From The Blind Watchmaker, where Dawkins describes the program, its performance suggests that it could be either of these options (though he doesn’t say).

On the other hand, from a (video-run of the program , go to 6:15), it seems to be the latter.

It’s easy enough to settle this question: Make the code for the program public. Perhaps Richard Dawkins himself or his friends at RichardDawkins.net can finally provide this code (apparently a program written in BASIC).

The prize is a copy of either Stephen Meyer’s new Signature in the Cell or Richard Dawkins’ soon-to-be-out The Greatest Show on Earth.

Should the winner choose the latter, I will ask Dawkins’s publicist to mail the copy. Given that at his site, he calls himself “the most formidable intellect in public discourse,” I would assume that if he signs the copy, it will be worth millions.

But wait. Let’s see that code first.

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377 Responses to Uncommon Descent Contest Question 10: Provide the Code for Dawkins’ WEASEL Program

  1. Scientists, when they write computer programs and make scientific claims based on their performance, are supposed to make the code available. Thomas Schneider has done this with EV. Christof Adami has done this with AVIDA. It is simply unconscionable that over 20 years after the program has been out and used to argue for Darwinism, Dawkins still has not made this code publicly available.

  2. kibitzer,

    I’ve heard it reported that there was a time when the code was in fact available, but I can’t verify the veracity of this claim. We’ll see if it turns up.

  3. A single Google search has turned up 3 different listings of source code for the “Weasel” program written in 3 different languages, 1 of which includes both a locking and a non-locking mechanism built into it for easy comparison. All three show up on the very first page of results. Are you really having difficulty finding any source code for the Weasel algorithm? Or are you trying to pretend that the algorithm that he describes is completely irrelevant and it’s his original code written by him and him alone that’s really important?

  4. Atom,

    I’m not sure I’m being too hard on Dawkins. Granted, The Blind Watchmaker and his WEASEL program came out in the 80s before easy dissemination of the program code on the Internet would have been available. But the program has been much discussed on the Internet in the last decade. So where is the code?

  5. KRiS_Censored,

    Three different languages? Were those all written by Dawkins? What was Dawkins’ original code that he cited in The Blind Watchmaker. You make it sound as though the original code is unimportant. It’s the original code on which his inflated claims are based. Let’s see it.

  6. So, you want Dawkins to provide you with a 23 year old computer program that has probably been reproduced hundreds, if not thousands of times, in a variety of programming languages, including by one regular contributor to this site (Atom). Have I got that right?

  7. I have written a few programs in the nineties. Some even for university stuff. I have no copy left. I guess I lost a bit everytime I changed to a new OS or Computer.

    Anyway, the algorithm as described in the BW is enough to reproduce and many people have done so. This includes Atom from this very site (“Proximity Reward” algorithm from the tool on the EIL site).

  8. Oh, and btw, the BW is not presenting original scientific research in this case. Weasel is a pet algorithm developed for a popular audience almost 25 years ago – it´s scientific relevance is more or less zero.

  9. Indium,

    “It’s scientific relevance is more or less zero.” Since Dawkins used it to support evolution, are you saying that evolution is unscientific?

  10. Dawkins describes his algorithm in the following way:

    It again begins by choosing a random sequence of 28 letters, just as before:

    WDLTMNLT DTJBKWIRZREZLMQCO P

    It now ‘breeds from’ this random phrase. It duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL. [...] the procedure is repeated.

    This is enough to replicate his program:

    1. chose random string
    2. copy string n times with mutation. NOTE: at this step you don’t know which letters are correct in place, so no letter is safe from being mutated!
    3. chose best fitting string. NOTE: best fitting seems to be generally understood to be the string with the most correct letters, the fitting is expressed by a number between 1 and 28
    4. Stop, if the number of correct letters is 28, otherwise
    5. goto 2

    The parameters which you can chose is the number of copies n, and the probability that a letter in a string is mutated, p. You may even chose another procedure of mutation – but keep in mind the NOTE of step 2.

    It’s really basic to realize steps 1 – 5 in the programming language of your choice…

  11. 11

    kibitzer

    You make it sound as though the original code is unimportant. It’s the original code on which his inflated claims are based.

    Apparently you are in fact “trying to pretend that the algorithm that he describes is completely irrelevant and it’s his original code written by him and him alone that’s really important.”

    As a matter of fact it’s the original methodology (or in computer speak “algorithm”) upon which his claims are based. The code itself was simply a way of demonstrating that methodology and is completely irrelevant.

    Let me ask you this, if he re-wrote the program today and it was exactly the same in every possible way, except that one variable was named “y” instead of “x”, would that program be unusable? The methodology employed by the program is identical in either case, yet the code used to do it is different. How about if he changed a “for” loop into a “while” loop? Again, the final program would be identical in it’s methodology, but the code would be different.

    It’s the methodology that’s of real import. The specific code used to implement it is irrelevant.

  12. a number between 0 and 28, of course…

  13. kibitzer: No. Evolution does not need Weasel as a support. It was a simple model to educate a broad audience about the power of cumulative selection 25 years ago. I don´t really understand your logic there.

    BTW, above I wanted to write “…the algorithm as described in the BW is easy enough to reproduce …”.

  14. Indium,

    “… is enough to reproduce …” I assume you mean “… is EASY enough to reproduce …” But what do you mean by “reproduce”? Do you mean, (1) Come up with the exact program that Dawkins wrote? Obviously not. (2) Come up with a functionally equivalent program? But that’s the question, isn’t it, whether the program ratchets letters or doesn’t? Without the original code it’s not clear whether a given piece of code is functionally equivalent? Or do you mean (3) Come up with any old program that’s close enough? In that case, I assume you’re okay with Dembski characterizing Dawkins’ algorithm as ratcheting correct letters. No, you say? Dembski was wrong in that characterization? Then provide the original code. Repeat after me: WE WANT TO SEE THE ORIGINAL CODE, WE WANT TO SEE THE ORIGINAL CODE, WE WANT TO SEE THE ORIGINAL CODE …

  15. @Kris_censored:

    Or are you trying to pretend that the algorithm that he describes is completely irrelevant and it’s his original code written by him and him alone that’s really important?

    The operative question here is, what algorithm did Dawkins use? That question has never been definitively answered, yet arguments for evolution have been made based on the program’s performance. The program’s relevance as a demo of what evolution-like processes can do depends on what algorithm was used.
    Having a public copy of the source code would allow everyone to verify what algorithm was used.

    If he’s lost the source code, he should say so. If he has it, he should publish it.

    I don’t think the Weasel program is now important as direct evidence for/against evolution, since more recent simulation programs have gone into much more detail and the algorithms have been published. However, the Weasel program is a familiar example to many people, and thus a useful reference point (which is why Dembski and Marks talk about it). Significant questions about the accuracy and relevance of Weasel-based arguments for evolution could be answered if the algorithm(s?) were published.

    But possibly Dawkins and his allies don’t like the answers.

  16. KRiS_Censored,

    Ah, it’s the METHOLODOLOGY that’s important. And how do you figure out the methodology without the original code. Are you clairvoyant?

  17. lars#15

    The operative question here is, what algorithm did Dawkins use? That question has never been definitively answered,

    Actually, it has. For example, a step by step implementation of the algorithm described in The Blind Watchmaker is available here:

    http://www.softwarematters.org/more-weasel.html

    A report of Dawkins stating that his program does not fix correct letters in place is here:

    http://austringer.net/wp/index.....r-sweater/

    A video of the algorithm running, showing that letters are not fixed, is here:

    http://www.youtube.com/watch?v=5sUQIpFajsg

    All of this information, and more, has been posted on UD repeatedly every time the Weasel algorithm comes up.

    yet arguments for evolution have been made based on the program’s performance.

    You’ve got it backwards, I’m afraid. The Weasel algorithm was used to demonstrate the power of mutation and selection over random search, in a popular science book published 23 years ago. It was used to describe one component of evolutionary theory, not to support evolutionary theory.

    The program’s relevance as a demo of what evolution-like processes can do depends on what algorithm was used.

    Indeed. If letters were fixed in place once correct, that would not be at all relevant to evolutionary theory.

  18. kibitzer#16

    Ah, it’s the METHOLODOLOGY that’s important. And how do you figure out the methodology without the original code.

    By following the very clear description in The Blind Watchmaker, of course. Many people have done so successfully.

  19. DeLurker,

    Of course, as programs go, Dawkins’ WEASEL is trivial and it’s easy enough to reconstruct something that’s close to it. But given the controversy surrounding it, let’s see the original program. Why is that so difficult?

  20. kibitzer#19

    Of course, as programs go, Dawkins’ WEASEL is trivial and it’s easy enough to reconstruct something that’s close to it. But given the controversy surrounding it, let’s see the original program. Why is that so difficult?

    The program was originally written in Apple BASIC over twenty years ago. Neither the language interpreter nor the computer itself have been available for some time. I suspect that, even if Dawkins has a copy, there are no disk readers still available for that format.

    The algorithm is very clearly described in The Blind Watchmaker. The only people I know of who have misunderstood it are Royal Truman, Dembski, and Marks. The only “controversy” I have ever seen over this simple, well documented algorithm is here on UD.

    Please read the full description of the Weasel algorithm in TBW and explain how anyone could come to the conclusion that letters are fixed once correct.

  21. It only evidence to support the idea that the BW weasel has a latching mechanism, is that it appears to latch.
    Many people have subsequently shown that this behavior is readily achieved by algorithms that do have any latching mechanism.
    Now if anyone wants to argue that Dembski and Marks are accurate in their characterization of the BW weasel, they need to explain the observed difference in behavior of the BW weasel and the partitioned search that D&M describe.

  22. Arrgh , English, that should be “The only evidence” and “algorithms that do NOT have any latching mechanism.
    Sorry

  23. DeLurker,

    You wrote: “Please read the full description of the Weasel algorithm in TBW and explain how anyone could come to the conclusion that letters are fixed once correct.”

    Glad you asked. Look at the output of the program in The Blind Watchmaker, and you find that once a letter corresponds to the target sequence, it doesn’t change. And sorry, the book didn’t refer to the subsequent 1987 video in which letters do change after they match the target.

    So the question remains, did Dawkins write the program so that it ratchets correct letters or not. I’ll grant you, probably not. But Dawkins’ throughout The Blind Watchmaker prefers “cumulative selection” to “natural selection.” Cumulative suggests ratcheting. So Dembski’s interpretation is hardly as far-fetched as you make out.

  24. kibitzer#21

    You wrote: “Please read the full description of the Weasel algorithm in TBW and explain how anyone could come to the conclusion that letters are fixed once correct.”

    Glad you asked. Look at the output of the program in The Blind Watchmaker, and you find that once a letter corresponds to the target sequence, it doesn’t change.

    You are not taking into consideration the full description of the algorithm. Looking at the most fit daughter strings every 10 generations is obviously very unlikely to show reversions.

    Please show how the full, clear, detailed explanation of the Weasel algorithm can possibly be interpreted to even suggest that letters are fixed once correct.

  25. kibitzer:

    But Dawkins’ throughout The Blind Watchmaker prefers “cumulative selection” to “natural selection.” Cumulative suggests ratcheting. So Dembski’s interpretation is hardly as far-fetched as you make out.

    “Cumulative” and “natural” are orthogonal. In nature, selection is both cumulative and natural. In WEASEL, it’s cumulative but not natural.

    As Dave Wisker mentioned in another thread, Dawkins explicitly stated what he means by cumulative selection, and it has nothing to do with latching. From TBW page 45:

    The essential difference between single-step selection and cumulative selection is this. In single-step selection the entities selected or sorted, pebbles or whateverthay are, are sorted once and for all. In cumulative slelection, on the other hand, they ‘reproduce’; or in some other way the results of one sieving process are fed into a subsequent sieving, which is fed into into…and so on. The entities are subjected to selection or sorting over many ‘generations’ in succession. The end-product of one genration of selection is the starting point for the next generation of selection, and so on for many generations.

    And Dembski’s interpretation, which he has maintained throughout the years, mutates every unlatched letter and involves no selection. This contradicts both the description of the algorithm and the output reported in TBW, so I would call it not only far-fetched, but clearly wrong.

  26. kibitzer, may I ask, what is your evidence FOR a latching weasel? The output tables of resulting strings?

  27. I always find it interesting when a darwinist uses INTELLIGENT DESIGN to try to prove some component of evolution….but here’s my stab at it…

    printf (“METHINKS IT IS LIKE A WEASEL “);

  28. do I win a prize????

  29. Denyse:

    From The Blind Watchmaker, where Dawkins describes the program, its performance suggests that it could be either of these options (though he doesn’t say).

    Then why does Dembski continue to say that it’s the former?

    Dawkins also doesn’t say whether WEASEL includes code that steals my credit card numbers. Until he provides the code, it’s a toss-up. Should I cancel my credit cards?

  30. Ladies and Gentlemen,

    We’re all beating our gums. Please, let’s see the original code. Why is that so much to ask? To paraphrase Ben Stein, Does anyone have it? Anyone?

  31. kibitzer, none of us have it. Have you asked Dawkins?

  32. kibitzer, I guess you may have missed my question. If you don´t mind: What is your evidence FOR a latching weasel? The output tables of resulting strings?

  33. Why does the original code matter?

    The fact is algorithms which use latching and non-latching have been coded by others and are easily found on the web. Do these programs prove anything of substance relative to evolution or intelligent design? I tend to think not.

  34. I have tried to reconcile the performance seen in TBW with the no-selection-partitioned-search described by D&M.
    D&M explicitly state that the mutation rate for correct letters is 0%, and they state the number of progeny = 1; they do not, however, explicitly state that the mutation rate (for unlatched letters) has to be 100% (I know, I am being generous in my reading of “so we take 26 new letters”). So I tried to adjust the mutation rate such that a partitioned search would perform in a manner consistent with the performance seen in TWB.
    Err, it cannot be done. Forget about latching, you cannot have a partitioned search that changes only one element in its first iteration, and reaches a solution within 43…

  35. kibitzer#30

    We’re all beating our gums. Please, let’s see the original code.

    As I noted above in #20, it’s entirely possible that the code hasn’t survived changes in technology of the past 23 years.

    Dawkins’ very lucid description of the algorithm, however, has survived. Please explain how that description can be logically construed to involve explicit fixing of letters in place once they are correct.

  36. I can’t speak for Dawkins of course, so I am in the position of offering external criticism. Like many here (presumably), I have been a programmer for several decades. The trivial nature of the Weasel “demonstration” is what irks me. It seems clear to me that the algorithm misses the mark in what it apparently seeks to show. I’d therefore like to propose an alternative, which might be closer to the mark in the sense of demonstrating natural selection from an evolutionary perspective.

    My first suggestion is that the number of mutations should be set to a value that is consistent with what we actually know about the frequency of mutations (i.e. the likelihood that any one letter would be mutated in any generation).

    My second suggestion revolves around the idea of using a dictionary (electronic of course). As the letters are ‘mutated’ in the text, sections of the text should be compared to the dictionary to see if they are a functional word. For example, if the string RIKE gets mutated to BIKE or to HIKE then that is now a functional bit of text and will be highly conserved. The possibility that it will be converted to LIKE (part of Dawkins’ preferred outcome) is now greatly reduced.

    These modifications would seem to go some of the way towards addressing criticisms of Dawkins’ algorithm, however the downside from his p.o.v. is (in my estimation) that the algorithm will now be extremely unlikely to produce “METHINKS IT IS LIKE A WEASEL” and so of course his purpose in introducing it in the first place, which is apparently to hide from the general public the very real probability problems that evolutionary theory must overcome, would be frustrated … and why would he want to demonstrate the very point he is trying to hide in the first place?

  37. Sorry, a bit OT.

    Here’s Dawkins near the end of the “weasel” chapter – referring to the other simulation. Oh the excitement! the drama!

    When I wrote the program, I never thought that it would evolve anything more than a variety of tree-like shapes… Nothing in my biologist’s intuition, nothing in my 20 years’ experience of programming computers, and nothing in my wildest dreams, prepared me for what actually emerged on the screen. I can’t remember exactly when in the sequence it first began to dawn on me that an evolved resemblance to something like an insect was possible. With a wild surmise, I began to breed, generation after generation, from whichever child looked most like an insect. My incredulity grew in parallel with the evolving resemblance… I still
    cannot conceal from you my feeling of exultation as I first watched these exquisite creatures emerging before my eyes. I distinctly heard
    the triumphal opening chords of Also spiach Zaiathustia (the ’2001
    theme’) in my mind. I couldn’t eat, and that night ‘my’ insects’ swarmed behind my eyelids as I tried to sleep.

    Of course, in the excitement of the action, it would be easy to miss the man behind the curtains operating the buttons and levers!

  38. 38

    tsmith @27,

    I know, right?

    I think I may be able to improve upon your code some:

    int main()
    {
    printf (”METHINKS IT IS LIKE A WEASEL “);
    }

    Look, I couldn’t resist.

  39. Okay:

    Mrs O’Leary, I can point to the EIL weasel programs and I do believe the software is available. But alas that is by Atom, and it is associated with Dembski not Dawkins.

    I can also point out that in 1986, the o/p of Weasel was showcased as cumulatively marching to the target, and with samples that in 200 of 300 places, and in EVERY case where a reversion was a priori possible, we never saw ONE reversion. Such a significant sample suggests that the o/p effectively ratchets its way to the target, ansd that the successful letters are therefore latched.

    The real issue is HOW, and the answers are that there are two ways: explicitly, and implicitly.

    The latter working by virtue of there being a match of pop per generation, mutation rate per letter ansd fulter to select even the slightest advance to the target. For under relevant cases, no-change members will be by overwhelming odds present, and so if 1 change members are frequent, no-change and one step increments will dominate in such a way as to preserve currently correct letters.

    Nor is this theory, there are actual runs that do that. (HT: Atom and EIL.)

    Now, in 1987, the video runs most definiteoly do not have the latching action that is credible for 1986. This is suggestive of detuning of parameters and possibly a different filter.

    That should not even be controversial, but since the ratcheting-latching issue highlights the targetted search that lies at the heart of Weasel, and this in turn turns it into a “misleading” –Dawkins’ word! — example, this has become a focus for red herrings and strawmen, soaked in ad hominems and ignited.

    Sad. But sadly revealing.

    GEM of TKI

  40. O’Leary:

    How will you tell if the code is genuine, given that it will be just pasted into this discussion?

    Should I just write out the algorithm Dawkins describes in Apple Basic and submit it? It would produce the results he published.

  41. kairosfocus#39

    I can also point out that in 1986, the o/p of Weasel was showcased as cumulatively marching to the target, and with samples that in 200 of 300 places, and in EVERY case where a reversion was a priori possible, we never saw ONE reversion.

    That is because the few strings shown in The Blind Watchmaker are the most fit daughter strings from every tenth generation.

    You’re doing your math incorrectly. Dawkins’ Weasel algorithm, unlike that used by Dembski and Marks in their recent IEEE paper, uses a relatively low mutation rate across all letters in the string and population size much greater than 1. Taking a typical population size of 200, the number of strings generated in 43 generations (the time required to converge to the target string in TBW), there were 8600 strings generated. Of those, only 4 were shown in the book.

    In his second run, the target was found in 64 generations, for a total of 12,800 strings, of which only 6 were shown.

    You are considering only approximately 0.047 percent of the strings in both cases. The likelihood of seeing a reversion is, of course, very low.

    Since the output shown in TBW clearly cannot be used to claim that correct letters are locked in place once found, please explain based on Dawkins’ description of the algorithm how you can possibly come to the conclusion that they are.

  42. BillB,

    I’m sure we would all trust if Richard D. himself assured us that the code in question was his original. Also, like the forged Air National Guard documents surrounding George Bush in “Rathergate,” it will probably be easy enough to tell if the code was written recently.

  43. After the “Accidental Origin of Life” contest question, I think the newxt few questions would be:

    1. Why are their still apes, if we evolved from apes and evolution is true?

    2. Why don’t dogs ever give birth to cats if evolution is true?

    But this latest one is almost as good.

  44. Whoops, haste makes waste. I meant:

    “I thought the next few questions would be:”

  45. 45

    Programs implement algorithms, and algorithms are not cooked up after the fact to describe what programs happen to do.

    Those of you familiar with commercial software development might think in terms of “That’s not a bug, it’s a feature.”

    Those of you familiar with Peewee Herman might think in terms of “I meant to do that.”

    Something I forgot to mention is the convenience of turning Dawkin’s algorithm into the algorithm Dembski and Marks analyze. This makes them look so bad. It is much easier to come up with the active information of the D&M algorithm than the Dawkins algorithm.

    If we ID proponents want to gain credibility, we are going to have to exhibit exemplary scholarship, not look for excuses for what we do. Demanding program code when the algorithm is the issue is really shabby excuse-making.

  46. Anthony09,

    In place of your list, let’s try

    1. Why are there still Darwinists given the pathetic state of their theory?

    2. Do Darwinists reproduce in the ordinary way or by parasitizing the wider public and by siphoning their tax dollars?

  47. it will probably be easy enough to tell if the code was written recently.

    Not really, so long as the person writing it knows how to write in apple basic (which I don’t) and doesn’t use variable names that relate to current events or trends then there is no way of telling. Typically variable names in a programme like this would be obvious things like ‘Population’ and this would be consistent with code written then, or yesterday.

  48. kibitzer#45

    Let’s try this instead (from my #20):
    “Please read the full description of the Weasel algorithm in TBW and explain how anyone could come to the conclusion that letters are fixed once correct.”

    You have yet to address this core issue.

  49. The amazing thing is that all agree that the WEASEL program is meaningless for anything and the concept of cumulative selection is meaningless in the scheme of evolution other than the trivial. But here we are debating this nonsense like the fate of the world depended on it. For one reason only. Whether Bill Dembski interpreted the original code correctly. There is this intense obsession by the anti ID people to impugn Bill Dembski in any way they can but in the process they end up revealing how intellectually barren they are.

    The anti ID people essentially admit they have nothing of substance to say. So have at it with these feeble complaints. Every comment just makes it easier for the pro ID people.

  50. BillB at 40:

    No use asking me.

    Everything I know about computers, I learned from WordPerfect 5.0 20 years ago, and have since updated to WordPerfect 12.

    But lots of cats here ARE computer whizzes, and will sure know if Dawkins is funnin’ them.

    You may wish to consider pasting Dawkins’s original code onto a Web page, in case you have problems with length restrictions or other problems in our combox.

    Ours is a good system but was not intended to accommodate long strings of code, so I can’t answer for what will happen if you try to do it that way.

  51. As a programmer, I can tell you that Dawkins’ weasel algorithm is useless as an argument for evolution. It is just a trick to impress fools because it assumes an end goal. Intelligent design is written all over it.

    Darwinian evolution, on the other end, has no end goal. It is dead on arrival.

  52. DeLurker:

    “Please read the full description of the Weasel algorithm in TBW and explain how anyone could come to the conclusion that letters are fixed once correct.”

    Using the description of cumulative selection along with the illustration using the weasel program (both in TBW), the only inference is one of a ratcheting process.

    Otherwise he should have chosen a better term like “lost, found, lost, found again, then lost, and found again selection”

    Or “back and forth selection”.

    Or the “whatever bloody survives selection”.

    Or better yet “badda-bing, badda-boom selection”.

    But that wouldn’t have misled the populace into thinking the blind watchmaker is something that “he” isn’t.

  53. Also the program is evidence for ID as ID can be reduced to nothing more than a targeted search- along with the resources required to reach that target.

  54. I guess I have to be counted among the group that wonders why having the original code is so important. Both latching and non-latching algorithms can be coded, the various parameters (such as mutation rate) set, and the algorithms analyzed.

    As a historical note, there is code that I wrote 20+ years ago that I no longer have, but wish I did. Neither the listings, nor the punch tape, survived.

    IMO, this is much ado about nothing. Is there something I didn’t understand?

  55. Joseph,

    Also the program is evidence for ID as ID can be reduced to nothing more than a targeted search- along with the resources required to reach that target.

    This makes no sense. Is Guitar Hero also evidence for ID?

  56. kairosfocus:

    Now, in 1987, the video runs most definiteoly do not have the latching action that is credible for 1986. This is suggestive of detuning of parameters and possibly a different filter.

    Keeping in mind that the video shows all candidates, not just the winners, do you see any correct letters being lost from one generation to the next? How can you tell?

  57. Joseph#50

    Using the description of cumulative selection along with the illustration using the weasel program (both in TBW), the only inference is one of a ratcheting process.

    Like kibitzer and kairosfocus, you are not addressing the full description of the Weasel algorithm as clearly and cogently explained by Dawkins in The Blind Watchmaker. Picking one term (“cumulative selection”) out of a two page explanation is unconvincing in the extreme.

    Please refer to http://www.softwarematters.org/more-weasel.html for an example of how to go through the details of the Weasel algorithm step by step to create an implementation. There is no way that I can see to come to the conclusion that the mutation operator has any knowledge of the target string. If you can logically defend that proposition, please do so.

  58. Any semi-competent programmer can implement Dawkin’s weasel algorithm.

    Here’s my version in Common Lisp – the language God used to create the universe – I’m pretty sure it behaves the same as Dawkins’ original.

    I used SBCL to run it, but any Common Lisp implementation should do.

    Note that in this version, you can make the target string be anything you want, just change it in the first defparameter. You can also change the mutation rate & population size to see how they affect the evolution of the string.

    Note that the copy-mutate function has no knowledge of the target string.

    ;;;;;;;;;;;;;;;;
    (defparameter target-string “methinks it is like a weasel”)
    (defparameter population-size 10000)
    (defparameter p-mutation 0.001)

    (defun count-matches (x y)
    (length (loop for n from 0 to (1- (length x))
    when (eql (aref x n) (aref y n))
    collect n)))

    (defun copy-mutate (x mutation)
    (let ((cp (make-string (length x))))
    (loop for n from 0 to (1- (length x)) do
    (setf (aref cp n) (if ( (setf new-score
    (count-matches (setf child (copy-mutate x mutation)) target))
    score)
    (format *standard-output* ” Best match so far (this generation) == ~D : |~D|~%” new-score child)
    (setf x child score new-score)))
    (cons x score)))

    (defun random-string (len)
    (let ((str (make-string len)))
    (loop for n from 1 to (1- len) do
    (setf (aref str n) (code-char (+ 32 (random 95)))))
    str))

    (defun weasel (&key (target target-string)
    (pop-size population-size)
    (mutation p-mutation))
    (format *standard-output* “Population size: ~D~%P(Mutation): ~D~%Target: |~D|~%” pop-size mutation target)
    (let (gen matches (gen-count 0) (leader (random-string (length target))))
    (format *standard-output* “Initial (random) string: |~D|~%” leader)
    (setf matches (count-matches target leader))
    (loop while (< matches (length target)) do
    (setf gen (best-match leader pop-size mutation target))
    (setf leader (car gen) matches (cdr gen))
    (format *standard-output* "Best generation ~D match == ~D : |~D|~%" (incf gen-count) matches leader))))

  59. This comment system doesn’t seem to know how to handle greater-than / less-than characters, so let’s try encoding them. You can also email me, and I’ll be happy to provide this as a text file:

    ;;;;;;;;;;;;;;;;

    (defparameter target-string “methinks it is like a weasel”)
    (defparameter population-size 10000)
    (defparameter p-mutation 0.001)

    (defun count-matches (x y)
    (length (loop for n from 0 to (1- (length x))
    when (eql (aref x n) (aref y n))
    collect n)))

    (defun copy-mutate (x mutation)
    (let ((cp (make-string (length x))))
    (loop for n from 0 to (1- (length x)) do
    (setf (aref cp n) (if (< (random 1.0) mutation)
    (code-char (+ 32 (random 95)))
    (aref x n))))
    cp))

    (defun best-match (x pop-size mutation target)
    (let (child new-score (score 0))
    (loop for n from 1 to pop-size do
    (when (> (setf new-score
    (count-matches
    (setf child (copy-mutate x mutation)) target))
    score)
    (format *standard-output*
    ” Best match so far (this generation) == ~D : |~D|~%”
    new-score child)
    (setf x child score new-score)))
    (cons x score)))

    (defun random-string (len)
    (let ((str (make-string len)))
    (loop for n from 1 to (1- len) do
    (setf (aref str n) (code-char (+ 32 (random 95)))))
    str))

    (defun weasel (&key (target target-string)
    (pop-size population-size)
    (mutation p-mutation))
    (format *standard-output*
    “Population size: ~D~%P(Mutation): ~D~%Target: |~D|~%”
    pop-size mutation target)
    (let (gen matches (gen-count 0) (leader (random-string (length target))))
    (format *standard-output* “Initial (random) string: |~D|~%” leader)
    (setf matches (count-matches target leader))
    (loop while (< matches (length target)) do
    (setf gen (best-match leader pop-size mutation target))
    (setf leader (car gen) matches (cdr gen))
    (format *standard-output*
    “Best generation ~D match == ~D : |~D|~%”
    (incf gen-count) matches leader))))

  60. OP, why is anyone hung up on Dawkin’s weasle programs? It’s ONLY purpose was to demonstrate stepwise build up of information. It’s was not meant as complete analogy of evolution. As Dawkin’s said in Blind Watchmaker:

    “Although the [WEASEL] model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection, although human vanity cherishes the absurd notion that our species is the final goal of evolution. In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success.”

  61. mike, I know why us “Darwinists” are so hung up with it: Because Dembski for some reason continues to misrepresent it. This fact is, btw, independend of the latching issue at hand. Dembski describes a partitioned search: No population, no selection, 100% mutation rate of incorrect letters. Dawkins describes a GA: He selects strings from a population using a fitness criterion. Incorrect letters have a biologically at least more or less realistic mutation rate <10%.
    Also, it is fun to see kf and others come up with rethoric herring oil soaked smokescreens like "implicit latching"!

  62. denyse, kairosfocus and reader from riesel, are you aware that you’re using the word “ratchet” instead of “latching”?

    Darwinian evolution does “ratchet” information into the DNA. It’s been described that way by scientists for decades.

    It does this ratcheting through the simple technique of making many copies of successful DNA strings and letting natural selection get rid of any unsuccessful mutations to those strings – such as restoring a former incorrect letter.

    This is EXACTLY what happens in Dawkins’ program or any other program that successfully mimics evolution. That is why Dawkins did not have to put any kind of latching into his program – the latching / ratcheting is inherent in Darwinian evolution and his program merely simulates one part of it.

    Spiny Norman: Dawkins wrote “Weasel” as a pedagogical tool to demonstrate how the cumulative selection that is used by Darwinian evolution is almost infinitely faster than the type of “all-at-once” selection that creationists and IDists typically use. (You know, where they calculate that it would take 20^100 tries to find a 100 amino acid length protein by chance or 4^150 tries to find a 150 base pair long stretch of DNA by chance.) Because it was a teaching tool, he selected a specific target for it to find rather than confuse the issue by cobbling together some sort of moving target.

    However, as I’ve written on this blog, if you re-write the program to look into an external file for the “target”, you can change that target whenever you wish and the program will continue to find the new strings just as quickly as it finds the fixed “Methinks it is like a weasel”.

  63. I don’t understand why so many here are arguing against letting Dr Dawkins release his program. Or I should say “programS.” Inspired by the many posts about this Weasel idea, I stopped at the library on my way home from work and picked up a copy of The Blind Watchmaker. It turns out that the Weasel program was written not only in Basic, but also in Pascal (see page 49).
    These would be fairly small programs, so it would not surprise me if Dr Dawkins printed them out when he first made them, as I used to do when programming in Fortan during that same time period.

    Finally, many thanks to kibitzer for advocating so strongly for the position of openness in these matters. You are not afraid to mix it up with people who don’t share your views. I dare say you could not be advocating this position better if you were Dr Dembski himself.

    Now, let’s see BOTH these original programs, to get to the bottom of these issues of demi-ratcheting, cumulative selection, and so forth.

  64. Joseph:

    Using the description of cumulative selection along with the illustration using the weasel program (both in TBW), the only inference is one of a ratcheting process.

    Otherwise he should have chosen a better term like “lost, found, lost, found again, then lost, and found again selection”

    Or he could have use cumulative, as in cumulative height, cumulative wealth…

    If he wanted to describe a letter locking mechanism he could have just said that once a letter is found the search for it is over.

  65. O’Leary:

    But lots of cats here ARE computer whizzes, and will sure know if Dawkins is funnin’ them.

    Ok, so a follow up question.

    Lets say Dawkins or anyone else posts some code, in the correct language, that produces the correct behaviour.

    If the code does not contain a latching mechanism, includes a population of more than one, and a mutation rate not fixed at 0 or 100, that applies to all letters … Will the judges here conclude that it is the correct code, or will they cite these differences between it and Dembski and Mark’s algorithm as evidence that it is a fake?

    I have a strong feeling that some here would.

  66. Onlookers:

    First, the bottomline: after many months of exchanges, it is clear that –absent a near-miracle — no credible Weasel code c 1986 [and yes, per CRD's statements in BW, the basic version ran across a lunchtime and the Pascal one did so in 11 seconds] will be forthcoming.

    So, what we have to deal with is a minor (but instructive) bit of real-world scientific analysis, as I have documented here, months ago now. That is, we have to look at empirical evidence that is not complete — here, published showcased samples of runs of generational champions c 1986, and descriptions — and come up with a reasonable best explanation, using replication of results as a good cross-check, e.g through Atom’s adjustable Weasel, here.

    Also, it seems that the exchanges aptly model the patterns of contention and conflict that often happen at the cusp of scientific revolutions, as the old order reacts with cognitive dissonance — and, often, rage and associated idea hit-man rhetorical tactics designed to restore the old order and defeat the new by “any means necessary” — to that which threatens to overturn their comfortable world.

    Let us note:

    1 –> The printoffs of sampled, showcased generational champions c 1986 show altogether 300+ letters, 200+ of which are of letters that were initially correct in the seed or which have subsequently gone correct.

    2 –> IN EVERY INSTANCE WHERE A LETTER GOES CORRECT IN ANY ONE GENERATION, IT REMAINS SO IN ALL FURTHER SAMPLES UNTIL THE PROGRAM HITS THE FULL TARGET.

    3 –> On law of large no’s [the correct form of the layman's crude "law of averages"], that strongly supports the inference that the samples do not revert because the generational champions preserve correct letters very strongly.

    4 –> Examination of Dawkins’ remarks on the program (and Joseph and I are by now tired of the dozens of times we have had to point out what should be obvious facts of basic reading of direct statements in rather plain English] support that observation:

    [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection

    5 –> Weasel is targetted search that rewards mere proximity of non-functional phrases through a process of random variation of a seed to create a population and artificial selection based on mere proximity to a set target.

    6 –> Weasel’s gain in performance over random search is therefore directly — though inadvertently — acknowledged to be due to ACTIVE INFORMATION. (Thus, the relevance of Dembski’s and Marks’ analysis.)

    7 –> And, the failure to use realistic degree of functionality as a threshold of preservation — note the dismissal of “single step selection” begs the question of first getting TO shores of function in large config spaces before climbing to peaks of performance.

    8 –> In short, the root issue is being distracted from and misrepresented then dismissed. No wonder Weasel is “misleading.”

    9 –> However, we still have to explain the behaviour of the run of generational champions as evidenced by teh showcased samples c 1986.

    10 –> CRD speaks of selecting slightest increments to target, which by virtue of the digital, alphanumeric character system, is one letter.

    11 –> Similarly, he speaks of “cumulative selection.”

    12 –> Cumulative, as a word, means: “Increasing or enlarging by successive addition.” The increment in question plainly being that of proximity to target, per the selection of the greatest relative advance to target for generational champions.

    13 –> Thus, Weasel ratchets towards the target. Ratcheting, being:” To cause to increase or decrease by increments.” (Implicit in that is the dogging action of a pawl, whereby progress is one-way.)

    14 –> Thus also, a ratcheted advance latches progress so far. Latching being: “To close or lock with or as if with a latch.” (In this case, correct letters of the generational champions in the showcased runs c 1986, credibly appear to latch.)

    15 –> Such ratcheting-latching cumulative progress to target of course first and foremost is NOT a de novo creation of complex functional information. For, the information is preloaded through the presence of a target and a cumulative progressive mechanism that step by step advances to an already present target.

    16 –> This latching action can be fairly simply achieved EXPLICITLY by using a masking filter:

    a] say, let letter correct = 1, letter incorrect = 0. Then with perfect match we have 28 as a metric, and with perfect mismatch, we have 0.

    b] So, we compare members of the mutated population of a given generation with the target, assigning to each one a metric string, with 1′s and 0′s to match correct or incorrect letters.

    c] closest to target becomes new champion, and the 1′s act as mask bits that block further mutation of correct letters. (After all, they are perfectly functional and would be preserved by “natural selection.”)

    d] Each new generation will at least preserve what has been achieved and the march of generations will cumulatively ratchet their way to the target.

    17 –> The result can also be achieved — for “good runs” — IMPLICITLY. In this case:

    e] when population size and per letter mutation rate are set so that with very high probability there will be no change members of the population, and single changes will prevail otherwise, e.g. 4% rate, 50 – 100 member population seems a plausible set of parameters — there will be a strong tendency to preserve progress to darte and/or to reward single step advances that do not corrupt already correct letters.

    f] with a suitable filter, the resulting trend will be to choose generational champions that are either the same or single step advances.

    g]the showcased 1986 runs hit target in 40+ and 60+ generations, supporting that about half the time, no-change was the generational champion.

    h] similarly, single step advances predominated the rest.

    i] but with other parameter values, various effects uch as substitutions of correct and incorrect letters, or reversions will occur.

    j] As already noted and linked, these patterns have been demonstrated through actual runs of Atom’s adjustable Weasel, from EIL.

    18 –> Under other circumstances, weasel will show quasi-latched behaviour with relatively rare reversions on correct letters [similar to how anglers who use baitcasters will know that a ratchet and pawl may begin to slip if the dog is worn].

    19 –> under yet other circumstances, far from latched behaviour will occur.

    20 –> It has recetnly been suggested that the 1987 run is simply showing all members of population, and is in a condition where champions will show fairly frequent reversion. this can be accounted for by a case of a Weasel that is detuned sufficiently for that to happen.

    21 –> But, the 1986 runs of champions — here, taking into reckoning CRD’s claim that he never wrote an explicitly latched weasel — would very easily be explained as “good” runs of a tuned set of parameters, so that we see latching action.

    22 –> Now also there has been much digital ink spilled over how Marks and Dembski in their recvent paper have distorted the weasel relative to CRD’s program.

    23 –> however, on p. 1055, they simply describe, exemplify and analyse a partitioned search. Whether such partitioning of runs of generational champions into the active search subset of the string and the locked in subset is achieved explicitly or implicitly makes no material difference tot he analysis of how many generations on average it takes to hit target or the associated probabilities associated with the injection of active information.

    24 –> And, no, M & D do not provide an algorithm for a weasel, just an analysis of the sort of run of champions showcased in BW, 1986, that shows latched behaviour based on targeted search; to deduce the effect of active information by comparison with the yardstick, random walk search.

    25 –> As CRD remarked in BW and as was cited above, targetted search’s injection of active information makes a HUGE difference, one that M & D provide a quantitative analysis for and thence a metric of active information injected.

    26 –> And the relevance of active information to Intelligent Design is that it gives us a mechanism for explaining the action and impact of intelligence.

    27 –> Intelligent search works batter than random search [or a search algorithm picked at random from a large pool of diverse algorithms] because the active information coming from knowledge and creative imagination sharply restricts the scope of search to a zone much more likely to be close to success than a blind process.

    28 –> Going back tot he flooded fitness function landscape model, we can also se that an intelligent search that is not successful can cotribute to success. (For, if the bottom of the sea of non-function slopes up towards the beach of function, partial success and trends of partial success can guide further intelligent search by sending warmer-colder signals and trends, i.e increments in active information through a beacon.)

    29 –> In fact, Weasel is an inadvertent example of this! (Non-functional nonsense phrases progress to target through gradual warmer-colder signals emitted by an algorithm that has a distance to target/success metric.)

    ++++++++++++

    Now, onlookers, let us observe and analyse how the Darwinist critics of the latching analysis respond to the above.

    GEM of TKI

  67. I don’t really understand why it is so important to get Dawkin’s original code – even if Dawkins never wrote any code, and just imagined up the algorithm, the fact that it has been reproduced by many different people and operates exactly according to his description would indicate that the idea behind it and the principles involved in it are correct.

    It’s like not believing that aeroplanes exist until you see the original blueprints for the Wright Brother’s aeroplane. It has been done, its been reproduced, it works.

    Atom’s code at http://www.evoinfo.org/Resourc.....elGUI.html
    for the “proximity reward search” is a faithful reproduction of Dawkins code – there isn’t any latching (run a few trials and occasionally you’ll see a correct letter being dropped).

    What else do you need? Dawkins described an algorithm (without latching), and Atom and many others have programmed an algorithm that behaves exactly how he said it would. Even if the code didn’t exist when Dawkins wrote his book, it does now, so the points he was making in regards to the search are valid.

    (note that the “partitioned search” is an incorrect model of Dawkin’s search).

  68. PS: Atom’s source code is available, through the linked GUI page, here.

  69. kf, what you write boils down to “Just from the output we can´t decide if latching was used, but we will assume it was anyway. Without any proof or any mentioning of latching in the explanation if Weasel in the BW we will assume Dawkins lies and the video from 1987 is a different and more or less faked algorithm. We have to admit that the algorithm is good enough to preserve good letters, as a smokescreen we call that implicit latching.”.
    The question is not if Weasel latches implicitly, we know that it does (for certain parameters) and that´s exactly the demonstration of cumulative selection.
    The question is wether Weasel latches explicitly or, put in another way, if it treats correct and incorrect letters differently during the mutaion routine. It doesn´t. It doesn´t need to. Dawkins said it doesn´t. A video that shows the algoritthm running with different parameters shows it doesn´t. Mutations are supposed to be independend of resulting fitness, so there would be no reason to let it latch. When it is decided which “gene” mutates, the algorithm does not know which letters are correct. The orakel, as D+M call it, does not return the exact correct letter indices, it just returns a total fitness value (as it should).

    From Atoms software suite, which algorithm do you think is representative of Dawkins´ Weasel and which one corresponds to the algorithm used by D+M in their paper?

    I further note that you still do not adress the fundamental differences:
    DM don´t use a population, they don´t use selection. Weasel uses both. It has to, otherwise it would not work. A fundamental difference if I have ever seen one!

  70. Indium:

    Clearly you have a problem with evidence-based reasoning.

    Here is the showcased 1986 o/p|:

    ___________

    >> 1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL

    1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL >>

    _______________

    1] Kindly find a case of reversion in the 200+ possible cases in the runs of champions above, where such could happen; or else discuss their absence cogently in light of the law of large numbers.

    2] Kindly compare CRD’s remarks on how the program cumulatively progresses to target (as already excerpted), demonstratin how reading the remarks as meaninfg what they say is not correct.

    Otherwise, you are simply “bravely” whistling by the graveyard in the dark; while the duppies leaning on the fence are looking on and shaking their heads.

    GEM of TKI

  71. kf, the absence of reversing correct letters is easily explained by what you call implicit latching*, eg the power of random mutation + selection. This is exactly what was supposed to be demonstrated by Weasel and is verified by what you say in your point number 17. Non reversing letters are no proof of anything. Since this is the only argument for latching you have you really have no argument at all.

    Since you still evade some important issues it is probably a good idea to remind you of them:

    From Atoms software suite, which algorithm do you think is representative of Dawkins´ Weasel and which one corresponds to the algorithm used by D+M in their paper?

    Main differences between the Partitioned Search and Weasel:
    D+M don´t use a population, they don´t use selection. Weasel uses both. It has to, otherwise it would not work. A fundamental difference if I have ever seen one!

    * I hesitate to use your “implicit” smokescreen, because incorrect letters are not protected from mutations when generating the next population, so there is no latching at all, just a successfull evolutionary search.

  72. PS: Here is Simon Greenleaf, a founding father of the modern theory of evidence, on the error of the skeptic, which I have descriptively tagged, selective hyperskepticism:

    ____________________

    >> [26] . . . It should be observed that the subject of inquiry [i.e. evidence relating to the credibility of the New Testament accounts, but also generally applicable to matters of fact on the balance of evidence] is a matter of fact, and not of abstract mathematical proof. The latter alone is susceptible of that high degree of proof, usually termed demonstration, which excludes the possibility of error . . . In the ordinary affairs of life we do not require nor expect demonstrative evidence, because it is inconsistent with the nature of matters of fact, and to insist on its production would be unreasonable and absurd . . . The error of the skeptic consists in pretending or supposing that there is a difference in the nature of things to be proved; and in demanding demonstrative evidence concerning things which are not susceptible of any other than moral evidence alone, and of which the utmost that can be said is, that there is no reasonable doubt about their truth . . . .

    [27] . . . . In proceeding to weigh the evidence of any proposition of fact, the previous question to be determined is, when may it be said to be proved? The answer to this question is furnished by another rule of municipal law, which may be thus stated:

    A proposition of fact is proved, when its truth is established by competent and satisfactory evidence.

    By competent evidence, is meant such as the nature of the thing to be proved requires; and by satisfactory evidence, is meant that amount of proof, which ordinarily satisfies an unprejudiced mind, beyond any reasonable doubt. . . . . If, therefore, the subject is a problem in mathematics, its truth is to be shown by the certainty of demonstrative evidence. But if it is a question of fact in human affairs, nothing more than moral evidence can be required, for this is the best evidence which, from the nature of the case, is attainable. Now as the facts, stated in Scripture History, are not of the former kind, but are cognizable by the senses, they may be said to be proved when they are established by that kind and degree of evidence which, as we have just observed, would, in the affairs of human life, satisfy the mind and conscience of a common man. [Testimony, Sections 26, 27, emphases added.] >>
    ____________________

    Selective hyperskepticism reveals itself — and simultaneously reduces itself to absurdity — by the fact of inconsistency and unreasonableness in demand for evidence on matters of fact.

    In this case, no-one would even be pretending that the o/p of Weasel 1986 as showcased did not show a latched, ratcheting pattern and/or that both explicit and implicit latching has been demonstrated [with code accessible for inspection!], apart from other extraneous considerations that are irrelevant to the weight/balance of evidence sufficient to decide an ordinary, unprejudiced mind.

    Or, the man in the Clapham Bus Stop if you will.

  73. 38
    HouseStreetRoom

    LOL

  74. kf, you are correct in that Weasel is a GA that exhibits latching behaviour, which can be achieved without any latching mechanism, for the reasons you outline in your point 17 and acknowledge when you say “samples do not revert because the generational champions preserve correct letters very strongly.” (#3) Isn’t it cool?
    You are also correct when you say (#23) ” on p. 1055, they[D&M] simply describe, exemplify and analyse a partitioned search. ”
    The ONLY issue in this particular round of Weasel Wars is that D&M mis-characterize Weasel, as described in TBW, and that this mischaracterization has been previously pointed out to them.
    It is obvious from the behavior of Weasel in TBW that it is NOT a partitioned search as described by D&M. A high school student can see this. Why then did the paper cite TBW as the source of the partitioned search?

  75. Indium:

    1] You now concede that IMPLICIT latching works. Implicit latching is real.

    2] You then attribute it — in the face of the explicitly tagetted search based on reward of mere proximity of “nonsense phrases” to the target — to “the power of random mutation + selection

    3] Onlookers, observe, not “NATURAL selection.” A telling omission indeed. In short, Indium cannot bring her-/him-self to explicitly acknowledge that the selection in Weasel is artificial and intelligent based on active information, and is not parallel to what is said of natural selection. (CRD concedes this in some “fine print.”)

    4] Indium, had you simply bothered to read the always linked app 7, s/he would have seen that on the balance of evidence and in particular a reported claim by CRD c 2000, the best explanation is that the evident latching is IMPLICIT.

    5] You then proceed to discuss irrelevancies. D & M use an illustration of what partitioning is, and provide an analysis that will apply to any march of generational champions that exhibits latching. That is, partitioning into the on-target and active search zones, however achieved, will have the same relevant mathematical characteristics. This I have already pointed out.

    6] In short, the analysis in the paper is independent of the algorithm, so long as ratcheting action shows up. Partitioning is a cognate of ratcheting and associated latching in a targetted search.

    GEM of TKI

  76. kairosfocus#66

    So, what we have to deal with is a minor (but instructive) bit of real-world scientific analysis, as I have documented here, months ago now. That is, we have to look at empirical evidence that is not complete — here, published showcased samples of runs of generational champions c 1986, and descriptions — and come up with a reasonable best explanation, using replication of results as a good cross-check, e.g through Atom’s adjustable Weasel, here.

    No, that’s not what we have to do. What we have to do is read Dawkins’ very clear explanation of the Weasel algorithm as written in The Blind Watchmaker. Here it is:

    So much for single-step selection of random variation. What about cumulative selection; how much more effective should this be? Very very much more effective, perhaps more so than we at first realize, although it is almost obvious when we reflect further. We again use our computer monkey, but with a crucial difference in its program. It again begins by choosing a random sequence of 28 letters, just as before:

    WDLMNLT DTJBKWIRZREZLMQCO P
    It now ‘breeds from’ this random phrase. It duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL. In this instance the winning phrase of the next ‘generation’ happened to be:

    WDLTMNLT DTJBSWIRZREZLMQCO P
    Not an obvious improvement! But the procedure is repeated, again mutant ‘progeny’ are ‘bred from’ the phrase, and a new ‘winner’ is chosen. This goes on, generation after generation. After 10 generations, the phrase chosen for ‘breeding’ was:

    MDLDMNLS ITpSWHRZREZ MECS P
    After 20 generations it was:

    MELDINLS IT ISWPRKE Z WECSEL
    By now, the eye of faith fancies that it can see a resemblance to the target phrase. By 30 generations there can be no doubt:

    METHINGS IT ISWLIKE B WECSEL
    Generation 40 takes us to within one letter of the target:

    METHINKS IT IS LIKE I WEASEL
    And the target was finally reached in generation 43.

    There is no rational reading of that description that could possibly suggest that letters are fixed in place once correct. All daughter strings are created by mutation of the parent and the mutation mechanism has no knowledge of the fitness of the resulting string.

    If you disagree, show how Dawkins’ own words can be construed otherwise.

  77. PS: The search used for the printoffs I have given in earlier threads is the obvious one: the proximity reward search algorithm. And this is the one that is probably closest in concept to — certainly thee 1987 algor, and with parameters co-tuned to give latching, probably the 1986 ones.

    PPS: An explicitly latched algor can also use a population of mutants in each generation and pick the closest to target, but that will make but little difference other than somewhat speeding up run to target. (Cases where a gen size of 1 is used are simplifications for convenience; but such should now be avoided as they will become targets for idea hit-man rhetoric.)

  78. kairosfocus#69
    You have apparently missed my explanation in #41 of how you are doing your math incorrectly. As I point out in that post, you are considering only approximately 0.047 percent of all the strings generated by Dawkins’ Weasel algorithm. It is not surprising that you don’t see a letter reversion.

    You need to read the entire description of the algorithm instead of referring to just a few sample lines of output.

  79. DeLurker,

    I am addressing the full description made by Dawkins and illustrated by Dawkins in “The Blind Watchmaker”.

    Again if he didn’t mean “cumulative” he should not have used that word.

    And his illustration of the process using WEASEL there is only ONE inference to be made- it is a ratcheting process.

    OTOH you have not provided anything from the book that would change nor challenge that inference.

  80. Also the program is evidence for ID as ID can be reduced to nothing more than a targeted search- along with the resources required to reach that target.

    yakky d:

    This makes no sense.

    It makes perfect sense if you understand ID.

    So what do you know of ID and how did you come to that?

  81. DeLurker,

    The weasel program is only concerned with the output.

    Nothing else is relevant.

  82. DL:

    Simply read the excerpt above and the runs as shown.

    The runs as shown together with the remarks on cumulative selection make latching and ratcheting a very reasonable and straightforward understanding of CRD’s words.

    Focus on the 1986 printoffs and the meaning of CUMULATIVE in its context.

    the general rule of hermeneutics is to take the plain meaning in context as the meaning, save where it makes no sense.

    And, plainly the obvious meaning — cumulative, ratcheting, latching action as Weasel moves to target — makes a lot of sense.

    GEM of TKI.

  83. Joseph#70

    I am addressing the full description made by Dawkins and illustrated by Dawkins in “The Blind Watchmaker”.

    No, you are continuing to focus solely on the word “cumulative” and are applying your own, very restricted, interpretation of what that word means.

    When climbing a hill, one cumulatively increases one’s altitude, even though an individual step may decrease it temporarily. With a genetic algorithm, one cumulatively increases fitness, even though one generation may be less fit than the previous generation due to the vagaries of the random number generator.

    I posted the full description of the Weasel algorithm in #75. Please show how that could possibly be interpreted, in context, as supporting the idea that letters are protected from mutation once correct.

  84. kf, I will happily admit that the algorithm is good at preserving correct letters most of the time. Call that implicit latching if you must, but this is just a distraction on your part.

    Since it is an artificial algorithm this is artificial slection. Or natural selection if you call CPU, harddisk and RAM the natural environment of algorithms! ;-)

    Since you admit, that the latching is implicit the answer to the original question of the thread “Does the program let correct letters vary?” is YES! Most of the time these variations do not show up because of the selection routine, but they are still mutated.

    Now, this is sorted then.

    The next question then is if D+M misrepresent Dawkins. Since they use explicit latching instead of implicit, since they use no population and no selection the answer is also “YES!”.
    I suppose that the active info concept can be applied to the real Weasel, and Random Mutation / Selection are indeed discussed in the paper! But discussing Weasel using a different algorithm where the only similarity is that it also preserves correct letters most of the time is a blatant misrepresentation.

    I ask again: Which algorithm from Atoms suite corresponds to Weasel and which one corresponds tpo the Partitioned Search discussed by D+M?

  85. kairosfocus#81

    The runs as shown together with the remarks on cumulative selection make latching and ratcheting a very reasonable and straightforward understanding of CRD’s words.

    Here are Dawkins’ actual words, again:

    It now ‘breeds from’ this random phrase. It duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying.

    Note that there is no suggestion of mutating only incorrect letters. It is a very simple statement.
    Dawkins continues:

    The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL.

    The selection mechanism is the only step of the algorithm that refers to the target phrase. The mutation mechanism does not. There is no explicit preservation of correct letters.
    It is very clear from a straightforward reading of Dawkins’ own words that Dembski and Marks have misrepresented the Weasel algorithm in their paper.

  86. BillB:

    Or he could have use cumulative, as in cumulative height, cumulative wealth…

    Without qualifying the word there is no reason to think that is how he used it.

    IOW if he is using a word in a way it is not generally accepted then it is up to him to qualify it.

    He didn’t so there is no reason to think he did.

    If he wanted to describe a letter locking mechanism he could have just said that once a letter is found the search for it is over.

    How he describes the difference between a random search and cumulative selection, especially given the weasel illustration, that is teh only inference to make.

    IOW there wasn’t any need to come right out and say it.

    And taken in context what others say about mutations:

    A mutation is a permanent change in the DNA sequence of a gene.

    There just isn’t any other inference to be had.

  87. DeLurker,

    You don’t get to tell me what I am doing.

    Also I am using the word “cumulative” how it is defined- the standard and accepted definition.

    If Dawkins is using it any differently than the standard and accepted definition it is up to him to explain that.

    As I said if Dawkins wanted people to know the reality behind evolution he would not have used the word “cumulative” and he wouldn’t have used a program in which the output is always equal to or greater than the input.

    IOW there isn’t anything in TBW that supports what you are saying.

    Nothing- not one word.

    If there were you would have posted it by now.

  88. PS: DL, I am focussing on the showcased runs c. 1986 [as you cirted but seem to have missed the sifgnificancfe of in 41], which is what is to be explained as factual data. That data contains 200+ letters whose values could vary from correct a priori, but do not. (If you look up the demonstrated runs starting here, you will see cases where such reversions with detuned parameters are possible, and how long they tend to persist. If reversions were at all common in the relevant runs, reversions should have been easily observable in a sample of 200+ characters: taking Np = 0.1, and N = 200, p = 5 * 10^-4.)

  89. DeLurker,

    There doesn’t have to be any explicit code for latching.

    Latching/ ratcheting occurs as a matter of course given a small enough mutation rate and a large enough population size.

    What part of that don’t you understand?

  90. Joseph#85

    Without qualifying the word there is no reason to think that is how he used it.

    IOW if he is using a word in a way it is not generally accepted then it is up to him to qualify it.

    The usage described by BillB is perfectly standard. It is your restricted definition that is not.
    Hundreds of programmers around the world have implemented the Weasel algorithm in a wide variety of languages, based solely on the material in The Blind Watchmaker. Based on that, it appears that yours is the idiosyncratic interpretation, unsupported by the actual text.

  91. Joseph#86

    IOW there isn’t anything in TBW that supports what you are saying.

    Nothing- not one word.

    If there were you would have posted it by now.

    I have, as have others, several times. Again, in Dawkins’ own words:

    It now ‘breeds from’ this random phrase. It duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying.

    The algorithm clearly specifies mutation without respect to the target string. That is the obvious reading of the text and the most biologically realistic mechanism.

  92. indium:

    D+M don´t use a population, they don´t use selection.

    You have said that before but never substantiated that claim.

    IOW that appears to be all in your head.

    Ya see if they referenced TBW, which they did, then it is a safe bet that they used the same stuff- population and selection- that Dawkins used.

  93. Indium:

    Red herring.

    the facts in evidence to be explained are the showcased runs of champions c 1986.

    These on good empirical reasoning, show latching, and we have provided two mechanisms that can account for it.

    FYI, the champions emerge not when we have mutated a seed 50 or so times, but when we have filtered for closest to target. Thus mut rate, pop size AND filter affect the production ocf champions.

    After the ingredients are mixed, we see that under certain circumstances, already correct letters will be strongly preserved — and that under others, they are most emphatically not.

    So, implicit latching is not a nullity.

    GEM of TKI

  94. DELurker,

    I know the strings mutate.

    That was never the question.

    Latching/ ratcheting occurs as a matter of course given a small enough mutation rate and a large enough population size.

    What part of that don’t you understand?

  95. kairosfocus#87

    DL, I am focussing on the showcased runs c. 1986 [as you cirted but seem to have missed the sifgnificancfe of in 41], which is what is to be explained as factual data.

    That is obviously what you are focusing on, to the exclusion of the clear description of the algorithm that contradicts your claims.
    Look at the description, not the small amount of sample output.

  96. Joseph#88

    There doesn’t have to be any explicit code for latching.

    Latching/ ratcheting occurs as a matter of course given a small enough mutation rate and a large enough population size.

    Fantastic! We’re in agreement!
    Since there is no explicit code for latching in Dawkins’ Weasel algorithm, the IEEE paper by Dembski and Marks misrepresents it.

  97. The usage by BillB may be standard but is also EXPLAINED.

    Dawkins did not explain cumulative as a process that could also lose what it had.

    Ya see saying that would noyt have helped his case.

    But I understand your position needs to redefine things on the fly.

    And I understand that commonly accepted definitions do not mean anything to you.

    But then again that is why your position is nonsense.

  98. DELurker:

    Since there is no explicit code for latching in Dawkins’ Weasel algorithm, the IEEE paper by Dembski and Marks misrepresents it.

    Except that Marks/Dembski never stated the program enlists explicit code for latching.

    However reading TBW and looking at the weasel illustration, a ratcheting process is easily inferred.

  99. Joseph,

    the only case of EIL providing an algorithm for Weasel is Atom’s adjustable weasel. (In the paper they are simply analysing the dynamics of ratcheted Weasel type programs; applicable to any latched version, implicit or explicit. But some strawman factories are running 24/7 at UD these days.)

    When they provide such a case, we can observe that EIL provides not only source code but text boxes for you to put in your preferred pop size and mut rate!

    Anybody prepared to bet that they did not do a LOT of simulation before sticking with what they know months ago was a controversial paragraph?

    If someone is, I have some prime, hot — hot, hot, hot! — real estate on Chances Peak Montserrat to sell for a great price . . .

    GEM of TKI

  100. Joseph#91

    Indium:

    D+M don´t use a population, they don’t use selection.

    You have said that before but never substantiated that claim.

    IOW that appears to be all in your head.

    Ya see if they referenced TBW, which they did, then it is a safe bet that they used the same stuff- population and selection- that Dawkins used.

    Read the Dembski and Marks paper, section E, Partitioned Search:

    Two of the letters {E,S} are in the correct position. They are shown in a bold font. In partitioned search, our search for these letters is finished. For the incorrect letters, we select 26 new letters and obtain

    OOT*DENGISEDESEHT*ERA*NETSIL. (21)
    Five new letters are found, bringing the cumulatie tally of discovered characters to {T,S,E,*,E,S,L} All seven characters are ratcheted into place. The 19 new letters are chosen, and the process is repeated until the entire target phrase is found.

    No population, no selection. Indium’s description is correct.

  101. I read the paper.

    Just because they do not explicitly say there is a population of size X and Y selection, doesn’t mean they didn’t use them both.

    Do you have the code they used?

    If you don’t then you just don’t know.

  102. Joseph#97

    However reading TBW and looking at the weasel illustration, a ratcheting process is easily inferred.

    You keep claiming this, but you have yet to support your claim with reference to Dawkins’ description of the algorithm in The Blind Watchmaker. The text is clear — mutation is independent of fitness. There is no ratcheting.

  103. DL:

    You are simply asserting that the world is as you wish it to be, not as it is.

    Denial is not a river in Egypt.

    Onlookers,

    Observe CRD again, as already excerpted — and recall the showcased runs show evident latching and ratcheting to go with these remarks:

    ___________________

    >> It . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed . . . . >>

    ______________________

    Compare the plain vanilla defn of “cumulative: “Increasing or enlarging by successive addition.” And you can refer above to the step by step discussion at 66. (One of the effects of objection waves, however irrelevant or distractive, is to bury substantial comments so that they are easily overlooked.)

    QED.

    Good day

    GEM of TKI

  104. KF,

    Had Dawkins printed outputs that showed character reversals he would have screwed up many readers.

    IOW people would have noticed the contradiction.

  105. Joseph#100

    I read the paper.

    Just because they do not explicitly say there is a population of size X and Y selection, doesn’t mean they didn’t use them both.

    Do you have the code they used?

    If you don’t then you just don’t know.

    They describe a single string, not a population. They mutate every incorrect letter, rather than creating multiple daughter strings and selecting the most fit. No population, no selection. How can you read it otherwise?

  106. PS: DL: “cumulative: “Increasing or enlarging by successive addition.

  107. DeLurker,

    1- In TBW the weasel program never shows a reversal of charcters. Not one reversal is shown.

    2- People reading the book would look up the word “cumulative” because “cumulative selection” is new (was new at the time).

    3- Putting the two together- the definition of “cumulative”, Dawkins description of slight improvements and the fact the illustration doesn’t show any reversals, the inference is clear. Cumulative selection is a ratcheting process.

    If it wasn’t he should have been explicit in saying exactly how it works.

    However had he been honest his point would have been lost.

  108. kairosfocus#102

    it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection

    The ellipses you inserted actually span quite a bit of text. The discussion of cumulative selection is not part of the description of the algorithm, it is part of the description of the results.
    The simple genetic algorithm described by Dawkins results in cumulative selection, without the mutation mechanism having any knowledge of the fitness function. That’s the entire point of the example.

  109. DeLurker,

    Do you have their code or not?

    I say since they referenced TBW they used the same stuff Dawkins used.

    A partioned search would be a selection process- keep what matches and mutate the rest.

    That is selection.

  110. Joseph#106

    1- In TBW the weasel program never shows a reversal of charcters. Not one reversal is shown.

    This has been addressed repeatedly by several people during the interminable discussions on this topic. See my #41 in this thread if you missed those explanations.

    2- People reading the book would look up the word “cumulative” because “cumulative selection” is new (was new at the time).

    People with average or better vocabularies would understand that “cumulative” does not mean “monotonically increasing.” If Dawkins meant to say that, he has more than sufficient writing skill to do so.

    3- Putting the two together- the definition of “cumulative”, Dawkins description of slight improvements and the fact the illustration doesn’t show any reversals, the inference is clear. Cumulative selection is a ratcheting process.

    Putting two incorrect assumptions together and ignoring the clear description of the algorithm might lead to any number of incorrect conclusions.

    If it wasn’t he should have been explicit in saying exactly how it works.

    He was, but no writer can protect against deliberate misreading.

    However had he been honest his point would have been lost.

    Unfounded accusations of dishonesty are not part of civil discourse.

  111. Joseph#108

    Do you have their code or not?

    Why would their code implement a different algorithm than they describe in the paper? If you’ve read the paper, please show exactly where they describe a population and selection.

    I say since they referenced TBW they used the same stuff Dawkins used.

    That is exactly the point under discussion. They describe a completely different algorithm, thereby misrepresenting Dawkins.

  112. Joseph,

    so, you believe that D+M use a population and selection?
    The wording in the paper is very clear:

    Two of the letters {E,S} are in the correct position. They are shown in a bold font. In partitioned search, our search for these letters is finished. For the incorrect letters, we select 26 new letters and obtain

    OOT*DENGISEDESEHT*ERA*NETSIL. (21)
    Five new letters are found, bringing the cumulatie tally of discovered characters to {T,S,E,*,E,S,L} All seven characters are ratcheted into place. The 19 new letters are chosen, and the process is repeated until the entire target phrase is found.

    The article could not be clearer: NO population, no selection.

    So, you now claim D+M use a differnet algorithm than the one they describe in the paper. Great idea, I love it!

  113. The math they use easily destroys your argument Joseph. Look at the formula for finding a letter after Q queries: This formula is only correct when there is no population but only single queries where every wrong letter is mutated.

  114. Joseph, thank you for making our point, viz. D&M’s Section E is misleading:
    “I say since they referenced TBW they used the same stuff Dawkins used.”

    And yet they did not.

    “Do you have their code?”

    No, I have equation (22) on p1055 which is mathematically correct ONLY IF the mutation rate is 100% and the population per generation is 1.
    (You will notice that the formula does not include a term for either parameter…bit of a give-away)
    Equation 22 can be easily adjusted to account for mutation rates other than 100%; but if you introduce multiple offspring in one generation, then the math is completely different. I believe D&M are aware of this fact.
    And even with variations in the mutation rate, equation 22 cannot be made consistent with the observed behavior of Weasel in TBW.
    Case closed.

  115. I took the string
    SCITAMROFN*IYRANOITULOVE*SAM
    and calculated a next generation using Dawkins’s algorithms with populations of 10,50 and 100 – and mutation rates of .04, .05 and .1. The tenth string in the list is the second generation given in the paper of Mark and Dembski. The differences with the first generation are in bold face:

    1. SCITAMROFN*IYRANOIEULOVE*SAM
    2. SCITAMROFN*IYRANOITULOGE*SAM
    3. ECITAMRI*N*IYZANOITULOVE*SAM
    4. SCITAMROFN*IYRANOITUL*VE*SAM
    5. SCITAMROFN*IYRANOITULOVE*SEM
    6. SCITAMOOLNOIYRAMOITULOVE*SEM
    7. SCITANROFN*IYYANOITULOVE*SAM
    8. SCITIMROFN*JYRANOITULOVE*SAM
    9. SCITAMROFN*ICRHNOITSLOWE*SAV
    10. OOT*DENGISEDESEHT*ERA*NETSIL

    Can anyone spot a difference in the design of the strings? Anyone? KF? Anyone?

  116. 116

    Forgive me if I’m oversimplifying, but doesn’t the line (in the LISP version):

    (defparameter target-string “methinks it is like a weasel”)

    demonstrate that the algorithm is not a good model of natural selection? It seems more analogous to front-loading to me.

    I think a more realistic test would be to see if a similar neo-Darwinian algorithm, with no target string, could produce a program that does anything useful — replicate itself, for example. How long would that take? What are the chances that it would complete the task within 10^150 CPU cycles?

    To put it another way, I wonder if it makes any sense to entertain the possibility that computer viruses, with their self-replicating and self-modifying nature, evolved solely and spontaneously by random chance and necessity?

  117. seanbutnotheard,

    you are right, natural evolution has no fixed target.

    Weasel can be and has been critized because of this. But mostly by people who don´t understand its educational purpose.

    Your example of a better genetic algorithm is a bit strange. Evolution works with mutating replicators, so the ability to reproduce is already there. Where did that come from? That´s a completely different question! -> Origin Of Life! Weasel does not address this of course.

  118. seanbutnotheard#114

    I think a more realistic test would be to see if a similar neo-Darwinian algorithm, with no target string, could produce a program that does anything useful

    That wouldn’t be biologically realistic. While biological evolution has no ultimate goal, it does have immediate goals. Dawkins makes this clear in the same chapter in which he describes the Weasel algorithm:

    Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection, although human vanity cherishes the absurd notion that our species is the final goal of evolution. In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success.

    That’s quite different from having no target at all.

  119. kairosfocus, a couple of items that you might want to stop ignoring at some point:

    - There is no need to argue about what Dawkins means by cumulative selection, since he tells us explicitly. Webster does not trump Dawkins on the question of what Dawkins means.

    - There is no evidence that the program in the 1987 video is any less “implicitly latched” than the 1986 program.

    - There is no required “matching” of parameters in order to have “implicit latching”. The lower the mutation rate, the better the latching, regardless of the population. The higher the population, the better the latching, regardless of the mutation rate.

    - I’m still waiting for you to show us how M&D’s math applies to “implicit latching”. What is Q?

  120. 120

    @ Indium & DeLurker,

    Thanks for the clarification, the purpose of the software makes a little more sense to me now; Its scope is limited.

    I’ll admit to not having read Dawkins as thoroughly as I should on the subject… which I will do before interjecting again.

  121. kairosfocus:

    When they provide such a case, we can observe that EIL provides not only source code but text boxes for you to put in your preferred pop size and mut rate!

    Yes, Atom covered all the bases in his code. But turn to the Weasel Ware page. Here we find a mathematical description of what is explicitly claimed to be Dr. Dawkins’ search, but the math contradicts both the description and the output in TBW.

  122. 122

    What’s the big deal? This algorithm is so simple I can create a version of it in Excel, and I did:
    http://dreadtomatoaddiction.bl.....easel.html

    It works too. No latching, no active information, just a crude random search.

  123. Rob (and others):

    Re 119: Rob, kindly, read Eqn 22 p 1055, in its immediate context and tell me just what part of . . .

    Assuming uniformity, the probability of successfully identi-fying a speci?ed letter with sample replacement at least once in Q queries is 1 ? (1 ? 1/N)^Q, and the probability of identifying
    all L characters in Q queries is

    q = (1 ? (1 ? 1/N)^Q)^L (22)

    For the alternate search using purely random queries of the entire phrase, a sequence of L letters is chosen. The result is either a success and matches the target phrase, or does not. If there is no match, a completely new sequence of letters is chosen.

    . . . it is that you do not understand, as a mathematically sophisticated person.

    Again, once the run of generational champions takes on the cumulative progress, ratcheting-latching pattern [and cf the showcased runs of 1986 on that], it makes but little difference whether it is produced explicitly or implicitly.

    And, it has been SHOWN that it can do so implicitly, and the mechanism involved has been explained several times, hinging on the very high odds of a no-change case being present once we have a sufficiently large po per generation, and with a sufficiently low odds of mutation that single letter changes are the dominant form for advances. And, the matching of parameters is relative to having these effects turn up.(Too much of the above critical commentary reminds me of Galileo’s opponents who refused to look through his telescope for themselves but were all too copious with criticisms.)

    For the rest, please read no 66 supra and make reference to the onward linked, esp App 7 the always linked, which gives the background context for why there is a controversy since Dec last, and why the reality of implicit latching is important.

    G’day again.

    GEM of TKI

  124. kf, the point is that eqn 22 does not (and cannot) take generational champions into account. The generation size is one. Given this fact alone, the algorithm described in section E is unrelated to the Weasel in TBW.
    Latching, whether mechanistic (“explicit”, IYW) or behavioral (“implicit”, IYW), don’t enter into it.
    D&M are wrong.

  125. kairosfocus, so you’re saying that Q is the total number of queries, and not the number of generations. Thank you.

    For WEASEL with a population of 200 and mutation rate of 5%, empirically the median number of generations is 45. Let’s see if the math agrees.

    q = (1-(1-(1/N))^Q)^L
    = (1-(1-(1/27))^(45*200))^28
    = .9999999999something

    But empirically it should be .5. Do you still hold that D&M’s math applies to algorithms that latch implicitly?

  126. 126

    KF writes> And, it has been SHOWN that it can do so implicitly, and the mechanism involved has been explained several times, hinging on the very high odds of a no-change case being present once we have a sufficiently large po per generation, and with a sufficiently low odds of mutation that single letter changes are the dominant form for advances. …

    This only makes sense under a scenario where the target string is known, and a very restricted view of the population of potential changes.
    If we have the target string “METHINKS” and start with the random string “QWERTYUI”, then a single mutation to “KWERTYUI” is no gain. It is also no loss. Retaining this mutation, suppose a second mutation happens to give us “KWERTYUH”, also no gain and no loss.

    Now suppose there is an alternate target “KENSMITH” which is equally viable. The second string “KWERTYUH” is effectively a double mutation towards “KENSMITH”. If our search is restricted to “METHINKS” this gets us nowhere, but with no predetermined target will now continue uphill towards “KENSMITH” instead. Under a different randomization the search might have reached “METHINKS” instead, or perhaps it could branch and both targets would be found. Speciation, anyone?

    The search never “sees” the target, only the hill. Forget the target entirely, the search is the thing.

  127. Through Google, I found Elsberry’s Javascript implementation of the Weasel program. When I ran it, it sure looked like it was ratcheting letters in place. However, I looked at the Javascript source code — and there was no provision for ratcheting. So, like random coder, I threw together some Lisp code to play with the algorithm.

    If the mutation rate and population size are just so, then the algorithm appears to latch. Increase the mutation rate and no latching behavior is observed. In fact, with higher mutation rates, the target string would likely not be found.

    Would it be too provocative to say that the mutation and population parameters have to be tuned by the programmer in order to get this to work?

  128. A few Footnotes:

    1] Weasel 1987:

    The proposal by Rob [that the BBC Horizon video is showing all pop members] would explain the winking effect on observed reversions, but at the price — as he implies — of removing it as evidence that implicit ratcheting/latching is presumably “not” happening.

    Hitherto, the 1987 video was usually cited by objectors tot he concept of latching as “proof” of non-latching behaviour. (Can anyone identify tehrun of generational champions from 1987 and show whether or not this run showed latching or quasi-latching [i.e. rare reversions of correct letters . . . probabilistic barriers are not generally 100% effective . . . ]?)

    Beyond this, it still remains that [a] implicit latching, [b] quasi-latching and of course [c] far from latching behaviour are demonstrated on adjusting mut rate, pop per gen and of course filter effects.

    2] When is a query a query?

    Notoriously, the Clinton era white House said that “it depends on wha the meaning of is, is.”

    We face just above [with reference to Rob etc], a situation where it depends on what a “query” is, in the context of the Dembski-Marks analysis.

    In short, the whole generation champion selection process can be legitimately seen as one query.

    For, if we have implicit latching happening — and remember latching-ratcheting relates to the run of champions . . . and that is D & M’s EXPLICIT context — in such a case, the Dembski-Marks analysis will apply.

    Thus, Q can legitimately be understood in context — StephenB keeps drawing our attention to this factor . . . — as a metric of number of generational champions in sequence. In short,t eh query ain’t over till the factor that is “ratcheting” has been identified. In the case of a procedure that enfolds population generation and proximity to target selection to get to that stage, the proper interpretation of Q is as number of generations of query.

    For — repeat — it is the generational champions that would be ratcheting to target.

    And, since a pop generation and champion selection procedure can be used with EXPLICIT latching, the same result applies for this case too.

    Next, partitioning is a term that describes a search procedure based on effective divide and conquer: once a partial success has been achieved, by whatever mechanism it is preserved and t5he rest of the search is confined tot he remaining part of the string. That can be done explicitly (cf mask filter concept in 66) or implicitly (see interaction of pop per gen, mut rate per letter in the seed for a generation, proximity to target metric, and filtering also in 66).

    In short, the associated objection turns on misreading what is going on in the analysis and in particular, misunderstanding of what constitutes a “query” in the contextually relevant sense.

    Ah. “Context . . .”

    3] When is a target a target?

    A glance at CRD’s description of Weasel should make it clear that he EXPLICITLY includes a proximity-to -target filter which promotes “nonsense phrases” — i.e. plainly non-functional ones — on a metric of proximity to a target.

    Let us remind ourselves [with special reference to TA], from BW:

    It [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection . . .

    This immediately implies that the target is preloaded in the algorithm, and is not created by it. (A GA version of Weasel that does not have a loaded target will not in general converge on the specific phrase “Methinks …” either.)

    That is, the analysis in 66 above and in the appendix it links, is correct.

    Also, t6he injection of targetting and of proximity reward as “fitness” rather than reasonable threshold of independent function — dismisswd as “single step selection” — inadvertently demonstrates that Weasel exhibits active information in action.

    GEM of TKI

  129. So, now, kf, you are reduced to claiming that an algorithm that does a query by constructing a population by copying a string with random mutations and then selecting the best fitting member is the same as an algorithm which gueries by just randomly selecting a new letter for every wrong one.

    This is so obviously wrong that it doesn´t even need a refutation. It is plain denial of the obvious.

  130. @wtf3:

    If you take number of correct letters as the fitness function, the probability of observing a change from a better to a worse state between two generations is dependent on the rate of mutation and the size of the population. As an example, for a mutation rate of 4% one gets:
    population of 10: 95.7 %
    population of 50: 0.0000026 %
    (pic)
    i.e., in a billion runs of Dawkins’s weasel program with a population size of 50, one expects 26 incidents of such obvious non-latching behaviour.

  131. Indium:

    Please.

    You force me to be direct: You need to stop misreading to object, and start reading to understand; for which reading in context in a conceptually and dynamically connected way is vital.

    (Contrary to the Dawkinsian propaganda, we are not ignorant, stupid, insane or wicked. Now, too, Marks is a PhD Electrical engineer, while Dembski is a PhD mathematician. As well, the paper — a peer reviewed publication of an IEEE professional society — presumably passed the scrutiny of a panel of at least three comparably qualified and experienced electrical engineers. As one who helped design an electrical engineering degree program, I can assure you that such men will have a solid background in mathematics and logical reasoning, as well as in modelling and analysis of mathematical models, and of course relevant computer science. In short, the attitude that ever so clearly lurks behind your objections does not pass the smell test.)

    So, it is no surprise that a closer look is revealing on the gaps in the objection you so facilely made. For just one instance, let us now observe the lead in to Eqn 22:

    . . . the probability of identifying all L characters in Q queries is . . . .

    1 –> That is, the natural point of completion of a query is the point where the issue of distance of approach to target is definitively addressed as at that time.

    2 –> This, plainly, is not the point where mutants in any given generation have simply been generated by the seed with the per letter mutation rate applied [that just gives us a cluster of n mutants].

    3 –> Instead, it is the point where you have applied the selection filter in the generation and have chosen a champion, identifying its Hamming distance to the target as the least. Probability metric q (the subject of Eqn 22) is then assessing the likelihood that one is then on target, i.e. ALL L LETTERS are then correct after Q queries.

    4 –> In short, just as I have already observed, the proper understanding of the point where a query is completed by the relevant algorithms is the point where you have a definite generation champion at a definite nearest distance to target so far.

    5 –> If the algorithm uses a generation population size 1, then it would be the immediate subject of the distance to target metric. But such a generation size is a simplification; CRD explicitly speaks of multiple member generations.

    6 –> And, it is when the champion on proximity to target has been chosen that we have something for which, across a sequence of generations, we may observe whether it ratchets (thus latches) or has occasional slips, or has no behaviour that looks anything like a ratchet.

    7 –> Recall, too, the further context of all this is the very explicit context in which: “char-acters are ratcheted into place . . . “

    8 –> In either an explicit or an implicit latching case, that can only happen after the generation champion has been chosen by the distance to target filter and a contest.

    _____________

    Therefore, I am not being “reduced” to anything. I am simply reading for sense in context; as opposed to reading to make — too often, specious and even sophomoric — objections.

    GEM of TKI

  132. PD: DIEB, re : If you take number of correct letters as the fitness function

    While I am aware of the ‘standard” terminology, I must point out how it is loaded and misleading here. For, the Weasel does not assess fitness in any sense of functionality. It only assess distance to pre-loaded target [i.e. Weasel is not creating de novo information out of noise!], rewarding “nonsense” — thus precisely non-functional and unfit — phrases for proximity. this is at the heart of the question being begged by the program, as I pointed out in 66 above, and of course in my always linked appendix 7.

  133. WRF3, 127:

    Re: >> If the mutation rate and population size are just so, then the algorithm appears to latch. Increase the mutation rate and no latching behavior is observed. In fact, with higher mutation rates, the target string would likely not be found. >>

    In short, under certain conditions, the algorithm will implicitly latch [a certain proportion of the time, quasi-latching otherwise one presumes . . . probabilistic barriers do not impose solid barriers], but under others, it will not.

    If we, a la CRD 1986, are looking for “cumulative selection” then we will showcase the examples that “best” illustrate steady ratcheting progress to target, and voila, the Weasel 86 published results:

    ___________

    >> 1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL

    1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL >>

    ______________

    We may observe in these decimated samples that of 300 + letters we observe 200 of letters that have gone correct and not one instance of such a letter ever reverting to incorrect status. On la of large numbers, it makes it morally certain that he programs — proudly announced as cumulatively selective — indeed latched success to date and ratcheted their way to target in these cases.

    this can be achieved explicitly or implicitly, by suitably matching pop size, mut rate and filter, and of course showcasing good results [which as you suggest may not be particularly hard to find].

    A mountain has been made out of a molehill since December last, and now that a peer-reviewed paper hasd been published with an analysis based on ratcheting, it is being exgended into a mountain range.

    But in fact, ever since 1986, it should have been obvious to conscientious commenters, that Weasel begged the main questions at stake, was fundamentally dis-analogous to the3 claimed mechanisms of chance variation and blind natural selection, and in fact showed intelligently designed artificial selection at work.

    Unfortunately, such substitution of artificial for natural selection and inference of dubious results traces all the way back to Origin of Species.

    Sad. Ever so sad.

    GEM of TKI

  134. kf,
    far from being irrelevant, how the query is done is exactly the algorithm we talk about!

    For D+M, a query is being done by randomly choosing new letters for incorrect ones. The probability to find the target after Q queries is given by Eq 22 in their paper.

    Dawkins looks for a champion of a pool of sequences he builds by copying a parent string with random mutations (which are independent of the letter being correct or not). The chance to have the complete target string reproduced differs greatly from Eq. Nr. 22 from the D+M paper and obviously depends on population size and mutation rates, which are not used in the partinioned search D+M apply.

    Different kind of query, different algorithm. And, it bears to be mentioned again: No population and no selction are used in the D+M paper. As I said, denying of the obvious. Quite funny, please go on with it. It makes your evasion and failure to admit a simple error all the more visible for everybody.

    Oh, and to complete my catalogue of open questions/remarks: In Atoms GUI, which algorithm corresponds to the partitioned search from the D+M paper and which search algorithm corresponds to Weasel? As a new bonus: Of these two, which one seems to use more active info?

  135. Indium:

    You are confusing a description of the EFFECT of ratcheting with the mechanisms that generate it.

    As has been shown, ratcheting can be achieved explicitly OR implicitly.

    ONCE RATCHETING EXISTS, THE MARKS AND DEMBSKI ANALYSIS APPLIES.

    Your basic error is that you insist on seeing an explicitly latched mechanism in the Dembski and Marks analysis, whilst in fact they are starting from the OBSERVED ratcheting and are working out its mathematical implications for such searches. (Their example is one of what ratcheting looks like, presumably after several generations. Note that one of Dawkins’ examples, the 43 gen run, starts with three correct letters that never revert. By generation 10, something like six letters are correct and thereafter they never revert, steady cumulative progress being made onward until by gen 43 all letters are correct. This example is of course in BW, which is referenced by M & D in teh context. )

    You are reading explicit latching INTO the analysis, not drawing it out of it.

    Again, kindly stop reading to object and start reading to understand, bearing in mind that you are dealing with reasonably experienced and qualified persons.

    That would save you from making gross blunders in criticisms, at least.

    GEM of TKI

  136. Indium, you beat me to it. But kf keeps failing to get the point, so to repeat:
    D&M describe a partitioned search with a generation size of one. Any algorithm that selected a generational champion would have a completely different equation to describe its behavior.
    kf does however bring up an interesting point when he popints out that this is a peer reviewed paper that has

    “presumably passed the scrutiny of a panel of at least three comparably qualified and experienced electrical engineers”.

    kf notes that

    ” As one who helped design an electrical engineering degree program, I can assure you that such men will have a solid background in mathematics and logical reasoning, as well as in modelling and analysis of mathematical models, and of course relevant computer science.”

    Ignoring the rather silly argument from authority here, I will note that “as a PhD who has published and has reviewed papers” the peer-review process is not perfect.
    As a reviewer, you usually would not bother to check the appropriateness of the citations. The reviewer assumes that the citation is accurate and appropriate. So an electrical engineer reviewing this paper is going to assume that ref[12] describes a partitioned search with a generation size of one. The reviewer assumes that the authors are honest.

  137. kf:
    ONCE RATCHETING EXISTS, THE MARKS AND DEMBSKI ANALYSIS APPLIES.

    This is just plain wrong.
    Eqn 22 does not describe the mechanism of Weasel, and it does not describe the behavior of Weasel. And the reason is that eqn22 requires a generation size of one; no selection of a generational champion is permitted.
    It is impossible to achieve the Weasel run of 1986 via partitioned search.

  138. DNA Jock:

    I see you can repeat the idea hitman talking points quite well. (And please, turn off the strawman and red herring factories: it should be clear that I am asking for a fair reading on the grounds that people of a certain background have a reasonable level of basic competence, not appealing to blind submission to the authority of peer review. [See what troubled waters reading to object lands you in?])

    Now, please observe what has been pointed out, most recently in 131, and explain how ratcheting is observable apart from after a single representative of each generation has been selected, and for sufficient generations that we may reasonably see non-reversion.

    And, tell me how the generation of a cluster of mutants from a seed and selection based on closest approach does not generate a SINGLE champion as representative per generation; as we may see listed in the printoffs from Weasel 1986.

    The D & M analysis occurs in the context of such observable ratcheting, and addresses the question in the first instance of probability of hitting home by Query number Q. And, the focus of that is the identification of the member of the latest generation which has least Hamming distance to target.

    Att hat point, once we have a viable mechanism to selecty a champion per generaiton, we have a basis for an analysis of ratcehting behaviour, which is what Dembski and marks undertake. They have said precisely nothing about how we get to the closest-approach string, only that it is in the context that such strings, in succession ratchet towards the target.

    It is others who have asked how can that be, and our answer, with demonstration — facilitated by Atom’s adjustable weasel produced and supported by the same EIL — is that Weasel algorithms can be latched explicitly or implicitly, and with algorithms that latch implicitly, that depends on matching of generation pop size, mutation rate per letter and proximity selection filter.

    And, we can show marches of implicitly latched champions, which would be the result of queries in the relevant sense, as discussed in 131.

    once we see the ratcheting, cumulative march to target in action, the M & D analysis applies.

    And so, onlookers, we again see the sort of problem Galileo faced: many of his critics refused to look through his telescope and examine the actual evidence on the merits as a basis for informed discussion. their idea hitman talking points were quirte persuasive to many who were schooled in their view of things, but lacked grounding in the evident facts.

    And here, the latest red herring and strawman models intended to dismiss the M & D analysis hinge on a distorted reading of what a query is in teh M & D analysis.

    of courese, all of this is w=ever so far form the real issue:

    1 –> M & D have produced a significant analysis that introduces Active Information solidfly to the world of peers.

    2 –> In so doing, they are accounting for the impact of itnelligence on the dcreation of fucntionaly specific complex informaiton

    3 –> this extends the existing analysis of ID.

    4 –> Last and least, Weasel c 1986 aptly illustrates the impact of such active information. indeed, without realising it, Dawkins says as much in BW:

    It [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection . . .

    5 –> that difference of course comes out of active information.

    Onlookers, I think enough has been said for now to help spot the gaps in the objectors’ latest set of idea hitman talking points.

    G’day.

    GEM of TKI

  139. kairosfocus#135

    You are confusing a description of the EFFECT of ratcheting with the mechanisms that generate it.

    As has been shown, ratcheting can be achieved explicitly OR implicitly.

    ONCE RATCHETING EXISTS, THE MARKS AND DEMBSKI ANALYSIS APPLIES.

    The behavior of ratcheting only exists for certain values of population size and mutation rate, and even then only probabilistically. As Indium points out in #134:

    Dawkins looks for a champion of a pool of sequences he builds by copying a parent string with random mutations (which are independent of the letter being correct or not). The chance to have the complete target string reproduced differs greatly from Eq. Nr. 22 from the D+M paper and obviously depends on population size and mutation rates, which are not used in the partinioned search D+M apply.

    The Weasel algorithm documented by Dawkins and the the partitioned search algorithm documented by Dembski and Marks are completely different and not amenable to the same type of mathematical analysis.
    Further, your statement

    Note that one of Dawkins’ examples, the 43 gen run, starts with three correct letters that never revert.

    is incorrect. You have no way of knowing if those letters revert because only the best daughter strings from every tenth generation are shown. With Dawkins’ clearly documented algorithm, it is mathematically possible for a reversion to occur. It is impossible for a reversion to occur in Dembski and Marks partitioned search.
    This brings us back to the core issue, namely that Dembski and Marks did mischaracterize Dawkins’ algorithm in their IEEE paper.

  140. kf, you are so fixated on the implicit or explicit ratcheting or latching, it´s amazing.

    Please acknowledge that everybody has more or less understood this latching behaviour. From the output strings in the BW we can´t decide which internal behaviour the algorithm has. So, for the moment let´s pretend the latching issue is solved.
    But, what we can see very easily just from looking at EQ. 22 is that the analysis from Dembski and Marks is not correctly describing Weasel. The formula, plain and simple, is an incorrect description of Weasel. I don´t even need to do any calculation to prove it, I just have to note that the behaviour of Weasel strongly depends on mutation rates and population sizes, which is of course not true or EQ 22 or the partitioned search D+M in general.

    So, D+M use a completely different algorithm, the math is plainly incorrect for Dawkins Weasel. It is correct only for the partitioned search they describe in the text.

    You can check this easily once you finally let me know which of Atoms algorithms is Weasel and which one the partitioned search. But since you have ignored this questions about 10 times now I guess you will do it an eleventh time, too, right?

  141. DL:

    Passing by.

    For the sake of onlookers, i will add some pointers.

    You have summarised implicit latching as though you disagree with me.

    As to he case of the 43 gen program, I think the sample was nearly 90 letters in the sample that go correct and in the samples never revet. I suspect that a 90 or so sample will be representative, of the program as a whole, especially as CRD used it to illustrate cumulative selection, which is of course a near synonym for ratcheting.

    In short, you are indulging here in selective hyperskepticism.

    Indium:

    Not at all, you are reading INTO the remarks on p 1055, an algorithm that is not there. the analysis is of ratcheting behaviour as observed, not of how it may arise — apart from the associated effect of partitioning [which is produced by latching whether implicit or explicit].

    This can happen explicitly and implicitly, i.e. the analysis of ratcheting is not algorithm-specific, but observation responsive. Implications of observed ratcheting, not inference to best explanatory mechanism.

    AND, you need to realise that for the past 6 or so months there have been wave after wave of objections tot he reality and significance of implicit latching, including some aspects of your remarks.

    Onlookers, hope this helps.

    G’day again

    GEM of TKI

  142. No, sorry, it doesn´t help at all because you just ignore every argument and question.

  143. Indium:

    I am not ignoring questions, I have answered them on the merits.

    Just, my answers do not fit your preconceptions.

    Why not pause and review the thread above back to say 131, and then go way back up to 66 and come back froward? (Not to mention my always linked, appendix 7.)

    While you are at it, reread pp. 1055 – 6 in the paper.

    Then come back on the issues.

    Okay, I really have to go now.

    GEM of TKI

  144. PS: Onlookers, do the same. is it fair to say that I have ignored “every argument and question”?

  145. Ok, let´s try again.

    Which of Atoms algorithms is the partitioned search and which one Weasel?

  146. 146

    KF:

    I was trying to point out that the search will work equally well for any equivalent gradient function. For this example the target is known and fixed, but that is not a requirement: The search will work equally well even if a specific target is unknown (granted we might not know immediately when the search is completed).
    My comments perhaps stray too far from the topic at hand, so I won’t pursue this line of discussion.

    However …

    It seems that the definition of latching and ratcheting being used is that of any successful search. By this standard any algorithm capable of climbing a gradient is latching and ratcheting, and that seems to included all possible search algorithms. What would it take to have a search algorithm that does not, implicitly or explicitly, ratchet and latch? I would suggest that an algorithm with non-zero probability of back-sliding (moving down the gradient instead of up) is not doing either.

    I confess some confusion about the concept of “active information”. It appears to me like any use of information from the local or global search environment is being considered to as “active”. This would then include all search algorithms other than a “blind” random walk, and I have a hard time considering that to be any sort of a search. Is there such a thing as a search algorithm that does not use active information?

  147. DeLurker,

    I know only a sample of outputs were shown in the book.

    In that sample we never observe a character reversal.

    That is a fact.

    Take that with the definition of “cumulative” and his description of cumulative selection, there is no reason to think that character reversals are possible.

    Yes intlligent agencies can take a step back in order to gain ground going forward.

    But the weasel program is not imitating intelligent agencies.

    IOW your deception is duly noted.

    And if deception is all you have to make your case then you have already lost.

  148. In the meantime you have ignored my question in two additional posts of yours, btw, kf.

    I will add a bonus question: Look at the number of queries Atom tracks for both algorithms. Do they match your definition = finding one champion is one query?
    This is rather irrelevant for the question wether D+M misrepresent Dawkins but it shows very nicely that you just make up your definitions as you go along.

  149. kairosfocus#141

    As to he case of the 43 gen program, I think the sample was nearly 90 letters in the sample that go correct and in the samples never revet. I suspect that a 90 or so sample will be representative, of the program as a whole

    and
    Joseph#147

    I know only a sample of outputs were shown in the book.

    In that sample we never observe a character reversal.

    You are both ignoring my #41 and #78 in which I show that you are considering only approximately 0.047 percent of the strings generated by a typical run of the Weasel algorithm. Looking only at the most fit string every 10 generations is unlikely in the extreme to show reversions.
    Look at the algorithm description. It is very clear.

  150. The Dembski/ Marks paper pertaining to a partitioned search uses a selection process similar to Dawkins in “WEASEL”.

    They also use a population of 1.

    They also appear to be using a very high mutation rate- 5 correct letters appearing in one whack.

    They do not describe the starting sequence.

    IOW yes I see issues with their algorithm if it was supposed to exactly mimic Dawkins’ “weasel”.

    That said I don’t believe that was their intent. Dawkins was trying to illustrate a different idea than Dembski/ Marks.

  151. OK, let’s imagine, just for the sake of illustration, that ref[12] described a Weasel program with an explicit latching mechanism.
    D&M would still wrong to equate ref[12] with a partitioned search.
    Eqn 22 describes a partitioned search. It cannot be used to describe a process that includes the selection of a generational champion. This has been pointed out to you a number of times, and yet you continue to assert.

    ONCE RATCHETING EXISTS, THE MARKS AND DEMBSKI ANALYSIS APPLIES.

    Stripping away the rhetoric, your argument appears to be “I cannot see the difference between eqn 22 (partitioned search) and a Latching-Weasel, therefore there is none.”
    This sounds like an argument from personal stupidity, but I’ll give you the benefit of the doubt here and blame Morton’s Demon.

  152. Joseph,

    admitting an error (even if it is not your own) is not usual here on this board, I applaud your honesty in #150.

    Cheers!

  153. kairosfocus:

    The proposal by Rob [that the BBC Horizon video is showing all pop members] would explain the winking effect on observed reversions

    The winking effect has been explained several times by various people in the WEASEL discussions. Are you just now taking note of it?

    but at the price — as he implies — of removing it as evidence that implicit ratcheting/latching is presumably “not” happening.

    No, it doesn’t remove it as evidence that implicit latching is not happening, because it never was such evidence.

    Hitherto, the 1987 video was usually cited by objectors tot he concept of latching as “proof” of non-latching behaviour.

    And we’re exactly right, because we have always used the term latching to refer to what you call explicit latching, and the video does prove that the letters are not explicitly latched.

    the proper interpretation of Q is as number of generations of query

    Earlier it was “tell me just what part of . . . Q queries . . . it is that you do not understand.” Now you’re saying that a query isn’t actually a single inquiry of the oracle, but rather a whole generation. Of course, that’s what you meant all along, right?

    But you seem to have not put much thought into this. How do you explain the fact that M&D’s math doesn’t take into account the population size and mutation rate?

    Let’s do the same math as #125 with Q=generations:

    q = (1-(1-(1/N))^Q)^L
    = (1-(1-(1/27))^45)^28
    = .003

    but it should be .5.

  154. Good idea, Indium, to point people to the EIL site, where they can see for themselves that partitioned search and Weasel are quite different beasts.

    My personal favorite – take parameters that produce kf’s “quasi-latching”, say gen size 100 and mutation rate of 10%, but then increase the length of the target string…At 57 characters, the partitioned search needs a median of 117 queries, but Weasel has gone past 36,000 (x100/gen = 3.6 MM offspring) without success.
    It is left as an exercise for the reader to find Weasel parameters that produce “apparent latching” but query runs over a thousand generations.
    Now, how do I adjust eqn22 to model these searches? That’s a puzzler.

  155. DeLurker:

    Nonetheless, the Weasel algorithm as described can, in fact, take a step back.

    Not as described by Dawkins in TBW.

    You continue to ignore the fact that Dembski and Marks mischaracterized the Weasel algorithm in their IEEE paper

    That is not a fact. And as a matter of fact the only inference one can take from TBW is that cumulative selection, as described by Dawkins and illustrated by the weasel program is a ratcheting process.

  156. DNA_Jock: Be careful! You have just proven that evolution is wrong! ;-)

  157. DeLurker,

    We cannot consider what we cannot observe.

    All we have to go by is what is in the book.

    That is why your comment in 41 is irrelevant.

  158. BTW by saying non-telic processes can mimic agency, that is very deceptive.

    Cumulative in a non-telic scenrio can only refer to “increasing by succesive additions”.

  159. Joseph,
    yes, evolution tends to keep positive mutations in the population and so does Weasel.

    From the output in the 1987 video you can see that this is not true for every individual member of the population though. This is in line with the explanation of Weasel in TBW: The mutation rate is independend of the resulting fitness. This is, btw, the most important difference between Weasel and the partitioned search from the D+M article.

  160. Oh, and btw, as far as I can see a few posts from DeLurker have been removed from this forum. This usually means that DeLurker has been banned, Joseph. So, you are probably arguing with an empty chair. This is easy (for most people, some even then mess it up!), but not much fun I suppose.

  161. Mrs O’Leary (and onlookers):

    It is clear that no authentic code by CRD c. 1986 in Basic or Pascal will be forthcoming. So, we will have to work with the showcased print-offs and with the descriptions he has given.

    I: The impact of Active Information

    CRD’s remarks in BW, 1986, bring out a remarkable key fact that we might easily miss in the clouds of digital ink above on all sorts of side issues and side-tracks.

    Namely, in 1986, Mr Dawkins inadvertently testified to the power of intelligent design over blind chance and necessity, and in so doing also testified to the impact of active information provided by intelligence in making a search for functionally specific complex information become feasible:

    ___________________

    >> It [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer [indirectly, the programmer!] examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection [i.e. "more than a million million million times as long as the universe has so far existed"] . . . >>
    ___________________

    a –> Weasel c. 1986 (and maybe 1987 too) is cumulatively progressive, targetted search that on the showcased sequences of generational champions, ratchets forward to the target [latching the already achieved successful letters, even if they are in "nonsense phrases"], through a filtering mechanism that picks the closest approach to target in each generation as the seed for the next.

    b –> It is therefore unsurprising that when CRD makes qualifying statements, he admits that Weasel “is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target.”

    c –> So, Weasel is by its author’s direct admission, misleading because it is foresighted, targetted search, search that rewards increments in proximity rather than of function [note his "nonsense phrases remark].

    d –> Likewise, he admits that if instead Weasel had to produce functionality before any hill climbing could begin, it would fail, exhausting the available search resources.

    e –> And so, we see what accounts for the relatively remarkable capacity of cumulative, targetted selection on proximity: information abovut warmer/colder has been given, allowing for proximity-climbing.

    f –> i.e., the active information injected by the intelligent designer of the program has had a dramatic impact on the capability of Weasel.

    g –> It is equally worth noting that CRD acknowledges: “In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success.” That is, present functionality is critical to the working of natural selection, and so the dismissal of “single step selection” rather begs the main question, and helps Weasel achieve an unwarranted degree of plausibility and influence of making it seem that chance variation and natural selection can credibly create novel complex functionally specific information.

    h –> So, Weasel needs to be put out to pasture as another exploded icon of evolution. (But ID-ers can then hire it back out of retirement as evidence of the power of active information based intelligent design.)

    ___________

    A bit of an irony, nuh?

    [ . . . ]

  162. Now, too, there are a few mopping up points that need to be addressed:

    II: The Dembski-Marks “Algorithm”:

    Above, much has been made of an alleged algorithm developed by M & D, and how it so far differs from the Weasel 1986, to the point where issues of academic misrepresentation have been hinted at in purple passages.

    However, especially given the fact that EIL hosts Atom’s adjustable weasel that makes its source code available — hint, hint, Mr Dawkins — and covers the various possible weasels admirably, this is a case of making a rhetorical mountain out of a mole-hill. A glance at the section of p 1055 of the IEEE paper will help us see why:

    _____________

    >> Partitioned search [12] is a “divide and conquer” procedure best introduced by example. Consider the L =28 character
    phrase

    METHINKS ? IT ? IS ? LIKE ? A ? WEASEL. (19)

    Suppose that the result of our ?rst query of L =28 charac-ters is

    SCITAMROFN ? IYRANOITULOVE ? SAM. (20)

    Two of the letters {E, S} are in the correct position. They are shown in a bold font. In partitioned search, our search for these letters is finished. For the incorrect letters, we select 26 new letters and obtain

    OOT ? DENGISEDESEHT ? ERA?NETSIL. (21)

    Five new letters are found, bringing the cumulative tally of discovered characters to {T, S,E, ?,E, S,L}. All seven char-acters are ratcheted into place. The 19 new letters are chosen,
    and the process is repeated until the entire target phrase is found. >>
    _____________

    1 –> First, the example is explicitly given to illustrate what partitioned search is like, and starts with a set of letters in 20, then immediately proceeds to vary all incorrect letters, giving us 21 with several more correct letters [itself rather unlikely and a clue that this is didactic, not an algorithm in progress], then says “the process is repeated until the entire target phrase is found.”

    2 –> Let us, just for argument, accept that this is meant to be a realistic algorithm, with partitioning and 100% variation of letters remaining.

    3 –> Now, in sampling with replacement, the idea is that once a letter may vary, it can take up any of the 27 available states. Of these, one is correct, and 26 are not. So, immediately, to plausibly gain a five-letter increment in proximity to target, a very large pool of mutant progeny would have had to be created so that far-tail highly improbable outcomes of multiple correct letters would show up among the generation of mutants.

    4 –> And, a proximity to target filter would then be required to select the closest to target, which –voila! — has five more correct letters.

    5 –> So, immediately, if an alleged algorithm is being shown, it is credibly based on a very large population per generation and a proximity to target filter. (And, as the demonstration at 237 in the March 26 Wm A Dembski thread in this blog on simulation wars shows, such a case would race home to target through picking multiply correct mutants. For, there, we may see how a 999 pop, 8% all-letters may vary case runs home in 22 gens.)

    6 –> Of course, such an imaginary algorithm would have to be explicitly latched. For as the case F from 239 in the thread — a 999 pop, 25% case — shows, with those high rates, reversions will otherwise make it hard to close the deal.

    7 –> “GOTCHA!” Nope: STRAWMAN!

    8 –> For, already, we have seen that the projected D & M algorithm shows that a ratcheting action will close to target, and that it implies targeted, proximity filtering based search that uses generations of sufficient size to see far tail population effects such as multiple go-correct mutations. And, that the projection is based on an illustrative pedagogical example rather than a sample run. So, there is plainly a caricature being set up to be knocked over here.

    9 –> On a more reasonable, less rhetorically loaded discussion, M & D used a didactic illustration of what partitioning means, and how a partitioned search ratchets, then analysed what that implies about active information and its impact on success.

    10 –> Now, we have long since seen from 234 in the Sim wars thread that such partitioning can be achieved not only EXPLICITLY, but also IMPLICITLY. Similarly, EIL just happens to sponsor Atom’s adjustable weasel, which provides explicitly latched search and a second algorithm that under certain cases — as in 234 Sim wars thread, etc — will implicitly latch as pop per generation, mut rate per letter and filter interact. [Observe how those objectors who so stridently claim to see an algorithm convenient to their debating points in the IEEE paper glide by the provision of the adjustable weasel as quickly as they can, even repeating silly questions on which algorithm was used to do the implicitly latched demonstrations even after it had not only been obvious but explicitly answered.]

    11 –> So, once we respect context, we can easily see that the illustration at p 1055 in the IEEE paper is didactic rather than a description of a serious algorithm.

    12 –> But also, we see that the illustration even taken as a caricature is actually going to have to imply a very large population per generation and aggressive proximity filtering that can capture cases where multiple letters advance.

    13 –> this is suggestive o0n a second point of debate as already addressed: what a “Query” means in the context of p. 1055. the answer is again plain, i.e my earlier analysis in what is now 131 is correct:

    . . . let us now observe the lead in to Eqn 22 [on p. 1055]:

    . . . the probability of identifying all L characters in Q queries is . . . .

    1 –> That is, the natural point of completion of a query is the point where the issue of distance of approach to target is definitively addressed as at that time.

    2 –> This, plainly, is not the point where mutants in any given generation have simply been generated by the seed with the per letter mutation rate applied [that just gives us a cluster of n mutants].

    3 –> Instead, it is the point where you have applied the selection filter in the generation and have chosen a champion, identifying its Hamming distance to the target as the least. Probability metric q (the subject of Eqn 22) is then assessing the likelihood that one is then on target, i.e. ALL L LETTERS are then correct after Q queries.

    4 –> In short, just as I have already observed, the proper understanding of the point where a query is completed by the relevant algorithms is the point where you have a definite generation champion at a definite nearest distance to target so far.

    14 –> So, there are no real — as opposed to strawman –barriers to looking at the M & D analysis as an analysis of partitioned, ratcheted, cumulatively progressive search for a target, however achieved: explicitly or implicitly.

    15 –> And that is what M & D present, and in so presenting they highlight the impact of active information coming from intelligent designers — including of course Mr Clinton Richard Dawkins.

    [ . . . ]

  163. III: Minor issues

    Several debate points have been raised that require a footnote or two:

    1] Latching must only be explicit:

    We have of course demonstrated that it can be implicit, especially when one is looking at showcased “good” runs.

    That is, if there is a big enough population and a small enough mutation rate that we have a high probability fo no-change members in each generation, and single step changes are otherwise significant, then with an appropriate filter, we can fairly easily observe cases where once a letter goes correct, it will remain so all the way to the target. (The first such demo used 4%, 50 on Atom’s adjustable weasel.)

    In short, latching, an aspect of ratcheted, cumulative progress to target, can be achieved explicitly and implicitly.

    2] What about quasi-latching?

    Since we are looking at showcased runs, it is the cases that show no reversions that become what we need to explain.

    The fact that — since, probabilistic barriers are inherently porous — other runs on the same parameters may show occasional reversions therefore makes no relevant difference. (I used the term quasi-latched to predict such cases, which have ALSO been observed.)

    3] Which Weasel shows implicit latching per Atom’s lists of algorithms?

    Already answered but recirculated as though unanswered: PROXIMITY REWARD SEARCH.

    4] Parsing EQN 22, p. 1055:

    In introducing the expression, M & D note: “Assuming uniformity, the probability of successfully identi-fying a specified letter with sample replacement at least once in Q queries is 1 – (1 – 1/N)^Q.”

    So, in this analysis, they are seeing letters in parallel columns of search, each in effect independent of the others. N is number of letters in the alphabet, and Q the number of queries completed. The probability of being right are 1 – that of being wrong after Q tries.

    Eqn 22 extends this to L letters, L the length of the phrase.

    But, there is an evident subtlety there. This can be seen in that each of the L letters is free to come home at any point up to and including the Qth query. (So, it seems we are working on the odds of hitting the target AT the Qth try, not the cumulative odds up to that point.)

    This is fine for the context of comparative purposes as is shown in EQN 23 — on the similar odds to get to the target on simple random search — and following but it makes for a subtlety if one is expecting the cumulative odds to that point.

    5] Partitioned search and weasel are different beats!

    Not so fast, pardnuh!

    Up to 2000, the information the public has had in hand was the showcased runs of 1986, and the description of cumulative targetted search. on this premise, it is reasonable — thus legitimate — to construct a weasel that uses the obvious mechanism, explicit latching.

    Subsequent to that time, we have had statements from Mr Dawkins and co that Weasel did not explicitly latch at any stage — but mo credible c. 1986 code. (And BTW, commenter Apollos on this site has shown that explicitly latched weasels can be programed to show reversions. ONLY CREDIBLE CODE WILL BE DEMONSTRATIVE, IN THIS LIGHT.)

    We have accepted the testimony on the presumption of charity, and have demonstrated that latching is feasible on an IMPLICIT basis. (Note, this makes no difference to the already discussed point that weasel demonstrates the power of active information, not chance variation and natural selection based on complex function.)

    An explicitly latched weasel is a legitimate interpretation of the information given. And that is part of the point of the EIL demonstration: many weasels are possible and they give various patterns of behaviour, sometimes convergent, sometimes divergent. And in particular, implicit latching is a point of convergence between explicitly latched partitioned search and proximity reward search.

    6] What about the BBC Horizon 1987 program?

    This has often been held to demonstrate that Weasel as originally coded did not latch. Of course, it now is apparent that the winking effect is possibly due to the video highlighting the members of generations, not the generational champions.

    A result that — as was acknowledged above by the commenter who raised it — is entirely compatible with: IMPLICIT LATCHING.

    Beyond that, the gap between 1986 and 1987 together with the demonstrated impact of shifting parameters on a proximity reward algorithm without EXPLICIT latching — we can get latching, quasi-latching and far from latched behaviour — indicates that the 1987 run does not ground a claim that Weasel c 1986 as showcased did not latch and ratchet to the target in a cumulative process.

    7] Somebody was banned!

    This occasionally happens at UD, generally for abusive commentary; i.e for good — though regrettable — reason.

    (For comparison, there was a recent case where Mr Barrett Brown — a columnist at HuffPo — made some slanderous remarks there. A UD thread was put up to discuss the mater, and it turned out that at HuffPo: (i) comments were very restricted as to length [250 words in response to nearly 3,000], (ii) critical comments were subject to suppression on non-transparent grounds, with no defensible reason, (iii) slander and abuse were tolerated and even encouraged there. On balance UD is the better forum by far.)

    ______________

    So, much of the above shows how Darwinist talking points can make the weaker appear the stronger case, to the unwary onlooker.

    So, let us take note.

    GEM of TKI

  164. Yowser.

    With reference to kf’s first post, where he points out (in his language) that Weasel uses tons of ‘active information’, i.e. it is better than a random search. He is making CRDs point for him. Thank you.

    In the second post, kf tries to deduce a lot from the fact that D&M’s exemplar goes from 2 hits to 7 in a single generation.
    He claims this is “rather unlikely” and concludes that both of the following must be true
    1) it is clearly a didactic example, and not a real sample
    2) it shows that their must be a “very large pool of mutant progeny would have had to be created so that far-tail highly improbable outcomes of multiple correct letters would show up among the generation of mutants”

    Obviously, these two cannot simultaneously be valid conclusions, but, not to worry, the premise is wrong: the chances of getting an iteration this good are one in 419, well within the bounds of reasonable ‘data selection’, given the time and computing power available….

    But the third post is the winner. Here kf argues that equation 22 describes the probability that the Qth query is correct, rather than the cumulative probability.

    But, there is an evident subtlety there. This can be seen in that each of the L letters is free to come home at any point up to and including the Qth query. (So, it seems we are working on the odds of hitting the target AT the Qth try, not the cumulative odds up to that point.)
    This is fine for the context of comparative purposes as is shown in EQN 23 — on the similar odds to get to the target on simple random search — and following but it makes for a subtlety if one is expecting the cumulative odds to that point

    Wow. Wow. Wow. This is so obviously wrong I don’t know how to explain it. Here goes: since (1-1/N) is less than one, (1-1/N)^Q tends towards zero as Q gets very large. Thus equation 22 tends towards 1 as Q gets very large (for any fixed value of L). It’s a cumulative probability distribution. As D&M make really clear in the text.
    To repeat : eqn 22 shows the cumulative probability that a partioned search will hit its target. It cannot be adjusted to account for a generation size greater than one. Go to EIL and compare “Proximity Reward Search” (Weasel) with “Partitioned Search”. Due to the way they cite TBW in their paper, D&M are claiming that these two beasts are the same, when they clearly know better.

    2,740 words, all heat and no light. I guess I was wrong about Morton’s Demon.

  165. Onlookers:

    Simply compare what I wrote and DJ’s critiques.

    See where the balance on the merits is for yourselves, and who is dealing with specifics vs who is making simple dismissals based on snippets out of context and caricatured.

    GEM of TKI

  166. Sorry about the bad link. Please go to the EIL site and compare the behavior of “Partitioned Search” and “Proximity Reward Search”.

    I lowered the mutation rate to 3% to ensure I still get kf’s so-called quasi-latching behavior with longer Search Phrases, and I had a lot of fun watching the Proximity Search get worse and worse (relative to the Partitioned) as I increased the length of the Search Phrase.
    Don’t trust either me or kf, onlookers, go and try it for yourself.
    D&M’s paper maintains that these searches are the same…

  167. I propose the following experiment:

    Take 100 programmer.
    Show them the two pages of Dawkins book.
    Ask them to realize the algorithm in the language of their choice in an hour of time.

    Then, we can see which percentage understands the algorithm to latch explicitly, which fitness function is used in general, etc…

  168. KF, I think we can now sum up your claims as follows:

    1-> An explicit, required, latching mechanism is the same as non-explicit, non-required, not-always-latching behaviour

    2-> A mutation rate that has to be between zero and one hundred percent is the same as a mutation rate that has to be either zero or one hundred percent

    3-> A population of one, where no selection can occur is the same as a population of many from which one is selected

    Now:

    many weasels are possible and they give various patterns of behaviour,

    Nonsense, many types of search algorithm are possible, they can use many different strategies and mechanisms, and produce different results. But they are all different types of search algorithm.

    WEASEL is an algorithm defined by Dawkins in The Blind Watchmaker. Many people have written software based on it, and others have made software inspired by it, but which employs different strategies. There is only one WEASEL though and it is described quite clearly by Dawkins.

    Onlookers will have observed that you have expended a huge amount of text over several threads trying to rhetorically and semantically get around the basic fact that Dawkins algorithm is different that Dembski and Marks. One could be forgiven for thinking that your inability to admit error is pathological.

    Contrary to your allegations, those of us who keep arguing this point are doing so because it is a matter of fact, not because we are trying to confuse and poison the debate, or because we don’t understand the issues, don’t read your posts properly or are trying to avoid specifics.

    The irony of all this is it makes no difference to the content of D and M’s paper if they simply removed the reference to The Blind Watchmaker, and replaced it with a correct reference to an actual peer-reviewed paper or an academic volume describing a partitioned random search, rather than referencing a crude pedagogical example in a popular science book.

    All this work just to avoid admitting that a Weasel is not the same as a Fox!

  169. Indium,

    The debate isn’t about “evolution”.

    It is about directed vs undirected processes.

    And even the most beneficial mutation has a better chance of becoming lost before it becomes fixed- especially in sexually reproducing populations.

    But anyway I have the book on order from the local library.

    I will have it next week and post again at that time.

  170. kairosfocus:

    So, once we respect context, we can easily see that the illustration at p 1055 in the IEEE paper is didactic rather than a description of a serious algorithm.

    That’s a nice theory, but it’s belied by the fact that both Dembski and Marks have stated that this algorithm is, in fact, Dawkins’ WEASEL algorithm. Dembski has been saying it for years, even after correction. The EIL website still says it.

  171. In the Blind Watchmaker video… you do realize that you can see the “correct” letters briefly change, right? In the linked video, around 6:24, you can see the K in METHINKS turn into an N, then an X, then an S, each for a fraction of a second. All of the letters flicker between correct and incorrect. Say what you will about the applicability or accuracy of Dawkin’s program, but it obviously doesn’t lock the letters once they’re right.

  172. 172

    kairosfocus,

    With friends like you, who needs enemies? Some of us ID proponents with genuine competence in engineering would like for you to stop with your obfuscation, just as we’d like for Dembski to admit once in a while that he made a mistake. You seem to think there’s huge value in the cultural war in presenting Dembski as an inerrant genius. I’d remind you that even the original Isaac Newton spent at least as much of his time on alchemy as he did math and science.

    In scholarly circles, unlike political circles, owning up to errors is a key part of gaining credence.

    The truly sad aspect of this run-around is that Dembski and Marks actually do analyze something like Dawkins’ procedure in their article. More on this in my next comment. But in the meantime I ask, why are you wasting so much energy on muddying the waters when there is more valuable work to address?

  173. 173

    Dembski and Marks actually do analyze something fairly close to the Weasel procedure in section III-F.2, “Optimization by Mutation.” There are several differences from what Dawkins describes:

    1. The target is specified over a binary alphabet.

    2. The number of offspring is limited to 2.

    3. The mutation rate is so low that in most generations both offspring are perfect copies of the parent.

    The difference in alphabet is trivial. The target is arbitrary, as in the Weasel problem, and may be set to a string of 1′s to reveal that the optimization problem is the heavily studied ONEMAX.

    Solving ONEMAX is easy, yet it is clear in Figure 2 that D&M’s simulation runs typically required a great many trials (the horizontal axis should be labeled “trials” or “generations,” but the runs are very long in either case). The reason is that the mutation rate is 5 in 100,000 bits, when the length of bit strings is only 100. In other words, few offspring are mutants. From an engineering perspective, appropriate to an engineering journal, it is absurd to perform a stochastic search in which most trials generate no movement in the search space. The simulation does nothing but to give evidence that the simplifying assumptions in D&M’s derivation of (28) do not introduce substantive errors, provided that the mutation rate is extremely low.

    It is worth noting in the caption of Figure 2 that D&M do acknowledge that the decreases in fitness they assume, in the appendix, do not occur actually do occur rarely — even with an incredibly low mutation rate. It should be obvious, though no one has mentioned it here, that the probability of a decrease in fitness increases with fitness of the parent. When the parent matches the target, the condition for a decrease in fitness is that both offspring be mutants.

    I believe that D&M would have done better not to restrict the number of offspring to 2, and to have obtained a low probability of decrease in fitness not by setting the mutation rate extremely low, but through a combination of a moderately low mutation rate and a somewhat higher number of offspring.

  174. kf, as expected you have once again not answered my simple questions. But your arguments are becoming more and more entertaining, if this it at all possible! And I am still trying to read all your stuff, so please keep it up.

    A small history of your arguments:
    - an algorithm that doesn´t protect correct letters in a search is the same as one that does (the famous implicit latching!)

    - an algorithm that does a query by replacing every wrong letter with a new random one is the same as one that builds a population (n>1) by copying a parent string with mutations and selecting the best one

    - you have redefined “query” to mean the determination of the next parent string. Everybody can look at Atoms GUI to see that you are wrong of course.

    - Somehow the paragraph/pictures/formulas in the D+M paper are only a pedagogical something that not criticizes Weasel directly but is somehow relevant anyway (this argument I don´t really get, I guess I am not alone here…). This obviously contradicts what Demsbi has said on this very website.

    Dr Dembski started a thread here where he explicitly said that his article criticizes Weasel and therefore evolution. I hope every onlooker now understands that he did nothing of the sort. He discusses a partitioned search which is completely different from the search performed by Weasel. Neither the explanation by Demsbki nor Eq 22 can be mapped onto Weasel and your inability to recognize this or maybe to admit this rather obvious problem is not reflecting well on you.
    I think your friend Joseph has now understood the difference, I think he has enough patience to explain it to you!

    So, I have to ask again, just for fun: Which algorithm in Atoms software suite is Weasel and which one the partitioned search? Are they the same?

    -
    @Oatmeal Stout
    Yes while the D+M can be criticized for not representing Weasel correctly that does not mean that the active info concept can´t be applied to Weasel. I am sure that it can be done in a similar way as it is done in the “Random Mutations” paragraph. Therere, however, D+M at least implicitly acknowledge where evolution gets its feedback (or active information) from: From the environment of course. But this is another topic.

    -
    @ Joseph
    It´s not about evolution? Yes, I agree.


    I have a brilliant idea: Why doesn´t Dr. Dembski present *his* Weasel algorithm here or just points us to the relevant code in Atoms suite? Maybe he can even get the prize then?

  175. 175

    2] What about quasi-latching?

    Since we are looking at showcased runs, it is the cases that show no reversions that become what we need to explain.

    The fact that — since, probabilistic barriers are inherently porous — other runs on the same parameters may show occasional reversions therefore makes no relevant difference. (I used the term quasi-latched to predict such cases, which have ALSO been observed.)

    So let me see if I have this straight. Latching (quasi- if you like) is still considered to occur even with occasional reversions. Hence you do not accept my suggestion that a non-zero probability of reversion is non-latching.

    How about this then: Latching occurs when the probability of moving “up” the gradient is greater than the probability of moving down. This would again seem to include any search other than a blind random walk.

    —and—

    Joseph wrote> It is about directed vs undirected processes.

    Is there any search other than a blind random walk that is undirected?
    That doesn’t seem like a useful distinction.

  176. 176

    Some administrative questions related to this contest.

    I have received no acknowledgment of my entry into the contest. Who may I contact about this?

    When is the closing date for entries, and are multiple entries allowed?

    How will the winner be determined?

    It IS a contest, right?

  177. 177

    There was an HTML failure in post #175: I was quoting kairosfocus at the beginning.

  178. Tomato Addict at 176:

    1. There is no acknowledgement apart from publishing in the combox here. We assume that if you do, you have implicitly entered. If you win, you must send me a mailing address to claim the prize, but it need not be your home and will not be harvested anyway.

    2. You can enter as many comments as you like, but you can only be one winner in a given contest. I have been known to declare two winners, in which case both get prizes.

    3. I usually judge the entries and my task journal reminds me when. With many entries, there could be delay. When the subject is technical, as in this case, I will seek help, possibly introducing more delay.

    4. We are all volunteers here. But yes, it IS a contest. There is a literal stack of books and DVDs right here in my office that will leave individually, when awarded.

  179. If anyone’s interested, Richard Dawkins himself has apparently commented on a recent thread PZ put up related to this contest. RD does comment on PZ’s blog from time to time, so I think it’s most likely really him.

    Anyway, RD says he no longer has the original program but that it did not “latch”. Not that latching vs. nonlatching is that important in the grand scheme of things, but it’s helpful to get confirmation of this detail from the source.

  180. First, the program was not part of scientific research – it was a demonstration of function. Second, many thousands have replicated the method and results without coding in explicit latching. Third, the discussion about a demo program as if it were research is absurd. Fourth, the original code is presumed lost. The point was never about the program, it was about the algorithm and how it demonstrates the effect of selection pressure on random changes.

  181. 181

    [My entry, made polite.] Let’s step through this “Weasel” controversy.

    1. Dawkins stated an algorithm.

    2. Dawkins claimed to have implemented the algorithm in his Weasel program.

    3. Dawkins provided a sample of the outputs from one run of the program.

    4. Dembski, observing that something possible in execution of the algorithm was not evidenced in the sample, inferred that the program did not implement the stated algorithm.

    5. Dembski went beyond this inference that the program did not correctly implement the stated algorithm to an inference of the algorithm the program actually did implement.

    6. Dembski and Marks attributed the inferred algorithm to Dawkins, giving no indication whatsoever that it was not the algorithm Dawkins stated, and went on to analyze it.

    Step 4 is logically invalid. Steps 5 and 6 are poor scholarship.

    Regarding step 4, the program is randomized, and the fact that something that might have happened appears not to have happened is not sufficient evidence for concluding that the program is incorrect. At best, one may question the probability that the program correctly implements the stated algorithm.

    Regarding steps 5 and 6, when you doubt that a program correctly implements an algorithm, you do not jump to abductive inference of the algorithm that the program does correctly implement, and then make your guess the topic of discussion. Proper conduct for a scholar would be to a) work with the author of the algorithm and program to determine if the program is correct, and b) develop a correct program if the original program is incorrect. It is never appropriate to say, “Well, let’s just change the algorithm to match the program.” Programs implement algorithms, and algorithms are not cooked up after the fact to describe what programs happen to do.

    Whether or not Dawkins has provided the Weasel program is utterly irrelevant. Dembski and Marks analyze an algorithm, not a program. The correctness of a mathematical analysis of the algorithm is independent of the correctness of any implementation of the algorithm.

    The appropriate challenge here is to provide the email in which Dembski and Marks ask Dawkins to confirm that the algorithm they attribute to him is in fact his algorithm.

  182. I should also add I wrote a short BASIC program coded for the Algorithm Dr. Dawkins explains in the Blind Watchmaker. It isn’t Dr. Dawkins’ original code, but it works the same as the sample shown in the 1987 video. I wrote it for the MS-DOS 3.3 version of BASIC, not Apple ][, but the differences should be minor.

  183. I gave up reading the detailed arguments a while back, but I think I’m right in saying that that kf (verbose chap, isn’t he?) accepts at this point that the original TBW program didn’t contain any explicit latching but gives the appearance of it because only every 10th generation is shown.

    I’ve observed this in my own (non-latching) implementation too, with n(offspring)=100 and p(mutation)=0.01. What’s interesting is that even if I print out the survivor for *every* generation, I still don’t see any reversion of previously correct characters to incorrect ones. Obviously the mechanism of selecting the fittest offspring from a suitably large population with a small mutation rate is a very powerful one. Which is what RD was trying to illustrate?

    Since it’s been shown over and over (and over) again that the algorithm he described produces exactly the results he printed in the book without any explicit latching, can someone explain to me why seeing the original source code is remotely important?

  184. Onlookers:

    Shaking my head . . . sigh.

    It is sadly evident from the above that we have much of straining at gnats while swallowing camels, as well as barking up wrong trees. Etc, etc.

    But first, let’s go back a moment to where I left off, on minor issues.

    I: More on Q

    One of the peculiarities of Weasel algors, is that they halt when they hit home; of course halting being a key property of algorithms. As a result, if they hit home before a generation number G, they do not get to G. Thus, if Q means number of mutants to date, then if size of generation is S, Q = G*S.

    Immediately, if a run completes [all L letters correct] at gen G, it cannot have been complete before G.

    So, the paper’s p.1055 discussion would on this reading of Q would be of a ratcheted run that shows a march of champions with latching up to G, when it halts: completion AT G. (In an explicitly latched Weasel this would be automatic, in a version that on being tuned and giving a good run latches — as observed [our first swallowed camel . . . ] — this implies that when metric falls to distance to target = 0, there is a latching action imposed.)

    And there is also the second camel: debates over the meaning of Q do not affect the OBSERVED FACT of latching (regardless of other runs that may not do so — remember, we are accounting not for typical or overall behaviour but for runs that are showcased c. 1986 that were showcased because of their cumulative progress to target).

    And that is camel no 3: implicit latching is an observed phenomenon, one that answers to CRD’s enthusiastic description and showcased printoffs. (The description and printoffs that the objectors above are ever so eager to direct our attention away from.)

    2: Camel no 4: distractions over code and algorithms

    The primary fact is that Weasel is a confessed, targetted search which makes cumulative progress to target, even through generations championed by “nonsense phrases.” Something which by CRD’s confession is “misleading” due to the long term targetting and associated artificial selection.

    Indeed, CRD also highlights that the targetting and artificial selection make a big difference to time to target: tha tis we have a case of active informaiton in action.

    This, we can see form BW, and it is apparently necessary to give it again, as last cited at 161:

    ___________________

    >> It [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer [indirectly, the programmer!] examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection [i.e. "more than a million million million times as long as the universe has so far existed" -- this is where CRD admits that active information has played a key role in the speedup] . . . >>
    ___________________

    As such, Weasel c 1986 as presented is “fair game” for an analysis as-is, on the implications of the active information manifested by such cumulative, evidently ratcheted and latched search on mere proximity not relevant complex functionality.

    And, since the analysis of ratcheted progress to target does not depend on whether the latching is or is not implicit or explicit — these are mechanisms to get to the observations of evident latched, cumulative, ratcheting progress to target c. 1986 — then, how that latching is achieved is irrelevant to the point that active information is a key reason for the performance above unassisted random search, and to quantify the injected active information.

    [ . . . ]

  185. 3: Selected bloopers (too many to address one by one . . . :

    a: BB@ 168: An explicit, required, latching mechanism is the same as non-explicit, non-required, not-always-latching behaviour

    –> Not at all: Strawman. (This, buy one who has already stepped outside the pale of civil discourse.)

    –> For the purposes of the M & D analysis, how latching is achieved for showcased runs is irrelevant. (remember, the issue is to account for the SHOWCASED runs, which will not necessarily be typical. [THAT IS PART OF WHY CRD'S CODE C. 1986 WOULD BE HELPFUL.])

    –> Once latching evidently exists, the analysis applies.

    –> And, let us recall: CRD in 1986 inadvertently admitted that the speedup was due to the targetting on proximity. That is, active information.

    b: A mutation rate that has to be between zero and one hundred percent is the same as a mutation rate that has to be either zero or one hundred percent

    –> Strawman, again. A caricature loaded with ad hominems is being set up.

    –> How latching is achieved is — for the purposes of the actual analysis — irrelevant to that it is achieved.

    –> This is now willful obtuseness, as well. [One who is involved in a civil discussion has a duty of care to seek to understand an interlocutor, not to twist words taken out of context to suit one's self. But then, sadly, BillB has long since demonstrated want of civility and a habit of twisting words self-servingly to accuse falsely.]

    c: A population of one, where no selection can occur is the same as a population of many from which one is selected

    –> Again, it is quite evident from p. 1055 as already analysed, that M & D gave a simplistic pedagogical example of what partitioning looks like. (Of course they did not reckon with the sort of word twisting rhetoric we are seeing in this thread and doubtless elsewhere. I am sure the IEEE engineers looking on are beginning to see what is wrong in the state of Darwinland.)

    –> A simple scrollup to 162 will suffice to show that a mutation of five letters going correct at once would only be plausible for a very large population indeed, with an aggressive selection filter. So, the notion of a population of one is read into the example, not drawn out of it and its context.

    –> And, the other half of this objection, that Q is number of mutants to date, then runs into the point that as discussed above, we would then have Q = G* S.

    –> the rest of BillB’s analysis collapses due to strawman premises.

    d: WEASEL is an algorithm defined by Dawkins in The Blind Watchmaker. Many people have written software based on it, and others have made software inspired by it, but which employs different strategies. There is only one WEASEL though and it is described quite clearly by Dawkins.

    –> from the above, it is clear that there are many legitimate ALGORITHMS for Weasel that will fit with Dawkins’ description c 1986.

    –> In short, this is mere caricature.

    e: Rob @ 170:That’s a nice theory, but it’s belied by the fact that both Dembski and Marks have stated that this algorithm is, in fact, Dawkins’ WEASEL algorithm. Dembski has been saying it for years, even after correction. The EIL website still says it.

    This is what The EIL page linked by Rob says: First, let’s look at partitioned search used by Dr. Dawkins. Assuming uniformity, the probability of successfully identifying a specified letter with sample replacement at least once in Q queries is . . . [leading up to the same summarised math as appears in p. 1055 of the IEEE paper]

    –> Of course, the “belying” is based on forcing the observation of partitioning — i.e evident cumulative, ratcheted search that advances to a target on proximity as showcased c 1986 — into a particular algorithm that implements it; and algorithm that does not appear in the IEEE paper, nor for that matter in the EIL page as linked.

    –> AND, we note that it is demonstrated that implicit latching is possible, which will produce the same run of champions effect as seen in the 1986 showcased run excerpts. [And if the 1986 run excerpts were ATYPICAL BEHAVIOUR (which is what some above suggest, while claiming that he program did not explicitly latch), then, that raises questions on the integrity of the Weasel program as presented at that time; questions that should be answered by opening to public inspection credible code. Recall, Joseph and I have been trying to account for the observed behaviour c 1986, on the claim that CRD did not explicitly latch his program c 1986. If implicit latching is possible but atypical, that itself raises questions about what was going on in the showcased 1986 runs. ]

    –> In short, more word twisting and strawmanising. With some troubling possible implicaitons that call for credible code c 1986.

    f: mb, 171: In the Blind Watchmaker video… you do realize that you can see the “correct” letters briefly change, right? . . . Say what you will about the applicability or accuracy of Dawkin’s program, but it obviously doesn’t lock the letters once they’re right.

    –> this of course raises the issue of the apparent gap between the showcased runs c 1986 and the video c 1987.

    –> the first serious option is that the 1987 video is a detuned run of Weasel that shows unlatched behaviour due to the detuning from the matched pop size, mutation rate and filter in 1986.

    –> the second [suggested by an objector to the idea of implicit latching], which does account for the winking effect, is that we are looking not at generation champions, but at the raw members of the population. (This runs into the problem that if MB’s observations are accurate, then mutation per letter rate is rather high — known to lead to one form of detuning and non-latched behaviour.)

    g: OS, 176:You seem to think there’s huge value in the cultural war in presenting Dembski as an inerrant genius

    –> Where have I ever said or implied such? [I think I am on record that we are all finite, fallible, and indeed fallen.]

    –> I happen to think that in this case, the M 7 D analysis — as opposed tot he caricatures presented above — is reasonable, and have given my reasons.

    –> And, pardon my suspicions when I see talking points of the now all too familiar form “I am a supporter of X, but I think the supporters of X are idiots or worse . . . “

    –> BTW, Weasel c 1986 is admittedly targetted search that rewards mere proximity.

    h: Indium, 174: an algorithm that doesn´t protect correct letters in a search is the same as one that does (the famous implicit latching!)

    –> Notice how this strawman distortion [cf bloopers a - c supra] has now become a repeated mantra, to be taken as gospel truth on the power of sheer brassy repetition in the teeth of the facts. [I shudder to think of what is going on in Darwinland echo chambers on this . . . ]

    –> Indium, in case you don’t recognise the tactic, this one is called the big lie, adn I need not list its well-known exponents — who BTW, projected it unto their intended victims, instead of telling the truth that they were the ones using it [in short, turnabout tactics].

    –> Please, don’t be taken in by it.

    –> And as for the “lost in the laugh” remark above, that too is a well-known agit-prop tactic. Stop laughing and start reading more carefully to UNDERSTAND before you criticise, please.

    [ . . . ]

  186. i: you have redefined “query” to mean the determination of the next parent string. Everybody can look at Atoms GUI to see that you are wrong of course.

    –> The problem at root is in the absurdities thrown out by trying to read the didactic example as an algorithm.

    –> Where I do have what I think on further thought overnight is an error, is that I have taken Q to be number of generations at the first, in that context. Q is — on second thought — number of generations multiplied by size of generations.

    –> And, that makes no difference to the evident pattern of ratcheting from generation to generation in the line of champions [which is what the printoffs c 1986 show; and what it therefore the empirical foundation of all discussion] that is a key part of the analysis, or tot he comparison of effect of active information based vs random search, as Q is in any case consistent across the two.

    j: Somehow the paragraph/pictures/formulas in the D+M paper are only a pedagogical something that not criticizes Weasel directly but is somehow relevant anyway

    –> Utter misrepresentation, laced with ad hominems. (Advice: If you do not understand, ask, don’t assert. Please.)

    –> A reading of 161 ff, for instance [not to mention all the way back to the always linked app 7] will easily and clearly show that I have said that the didactic example presented of what partitioning of a search looks like, is not a realistic representation of an algorithm, but a simple illustration of a behaviour of observed outputs: in ratcheted searches, once letters go correct they are preserved correct, and more and more letters go correct and are preserved until the target phrase is complete. [And, M & D say just about as much in pretty close words to what I have just said.]

    –> once that is seen, we can see the relevance and accuracy of the basic analysis of what such a ratcheted search looks like probabilistically, on the mere fact of ratcheting. (Which raises no commitments on what the ratcheting comes from, whether explicit or implicit.)

    –> And, I have said precisely nothing about the onward analysis in the IEEE paper, as this has not come up, i.e you are putting words in my mouth above, words that simply do not belong there.

    k: TA, 175: How about this then: Latching occurs when the probability of moving “up” the gradient is greater than the probability of moving down. This would again seem to include any search other than a blind random walk.

    –> Remember, we are starting form observing an evident o/p pattern, per showcased examples of “cumulative selection” in action.

    –> in those examples, for 200 cases were letters go correct, and can revert, the excerpts never show a reversion. And since listing every 10th generation’s champion is unlikely to correlate with the search process, then we can infer that the description and the showcased runs coincide: there is ratcheted progress to target.

    –> After that, we look a the “occasional slips” case; one that is also observed on producing a program capable with certain parameters being matched, of latching. this makes sense,a s probabilistic barriers are not absolute. [All the oxygen molecules in the room where you sit can conceivably rush to one end, leaving you choking; no physical barrier absolutely forbids that. But, that is rather unlikely, and unobserved.]

    –> And a third case is possible, where there is no evident ratcheting.

    l: YD, 179: RD says he no longer has the original program but that it did not “latch”. Not that latching vs. nonlatching is that important in the grand scheme of things, but it’s helpful to get confirmation of this detail from the source.

    –> And how did CRD explain the showcased runs and gushing remarks on the wonderful power of cumulative selection c 1986?

    –> Other than, that he is claiming that he did not EXPLICITLY latch the program, which would be the same thing he is reported to have said c 2000. [In short, the issue of implicit latching is still very much on the table, and recall, such behaviour on "good runs" is DEMONSTRATED. If CRD's actual o/p's on the showcased runs did not latch, implicitly or explicitly, then to present them as if they did while gushing on the power of cumulative selection will require a bit of explaining on how the results and remarks were not presented in a misleading manner.]

    –> In any case we have it that no credible code will be forthcoming. Contest over, unless someone can dig up a credible copy from somewhere that has a reasonable chain of custody.

    m: OS, 180:Dembski, observing that something possible in execution of the algorithm was not evidenced in the sample, inferred that the program did not implement the stated algorithm

    –> Bold denial of stated facts on the record.

    –> the claim by Dawkins p 48 ff of BW, was that Weasel exhibited “cumulative [and targetted] selection,” based on proximity to target, which conferred a major advantage over “single step selection.” Where, cumulative NORMALLY means: Increasing or enlarging by successive addition. [1st meaning AmHD.]

    –> in support of this, he produced listings c 1986 in BW and NewScientist, that showed over 200 cases of letters going correct and then open to reversion, without a single reversion in evidence; on two runs, one of 40+ and one of 60+ generations. [That OS thinks there was only one published run shows that he has not investigated carefully before commenting adversely.]

    –> On such — multiplying the two lines of evidence together — it is evident beyond reasonable dispute that Weasel c 1986 generational champions ratcheted to target with associated latching of successful to date letters on “good” runs.

    –> on “forensically” reconstructing the algorithm to do that, two main approaches are possible: explicit latching and implicit where the pop per gen, mut per letter rate and filter interact to at least some of the time give runs that ratchet. Both have been demonstrated and are legitimate readings on the evidence of 1986.

    –> on subsequent statements (and possibly the 1987 video] the latter is the — on balance of evidence — best explanation for the observed published runs and descriptions c 1986.

    –> the rest of OS’s case foes downhill from there, repeating a now familiar line of talking points.

    +++++++++++++

    After taking time to go through the above, I am still shaking my head.

    GEM of TKI

  187. PS: OS, If you rake time to look at my characteristic thought on ID [e.g through the always linked] in terms of functionally specific, complex information and its roots in thermodynamical and informational thinking (which trace back through Thaxton et al, not Dembski), as well as my related look at the Caputo case, you will see that my thought is significantly independent from that of Mr Dembski. I happen to think that Mr Dembski — though finite, fallible and fallen as we all are — has got some things right, things that are too often caricatured and wrenched by objectors to improperly dismiss them through strawman fallacies. And the habit of such strawmannising by denizens of Darwinland is I believe abundantly evident above.

  188. PPS: I also happen to think his partnership with Dr Marks has enriched his work. And, that on a topic known for months to be controversial, there would have been significant cross-checking before publication. Now, compare that with the sort of srtrawmannising above, and it should be evident why I draw the conclusions I do on who is more likely to be correct in this case. then, multiply by the obvious didactic example context of the alleged algorithm that they are being castigated for. And mix in the fact that explicitly AND implicitly latched weasel programs have been demonstrated on actual runs — programs sponsored on the web by the same EIL. After such factors are in evidence, what makes the best overall explanation? On what grounds?

  189. Kariosfocus

    –> on “forensically” reconstructing the algorithm to do that, two main approaches are possible: explicit latching and implicit where the pop per gen, mut per letter rate and filter interact to at least some of the time give runs that ratchet. Both have been demonstrated and are legitimate readings on the evidence of 1986.

    –> on subsequent statements (and possibly the 1987 video] the latter is the — on balance of evidence — best explanation for the observed published runs and descriptions c 1986.

    Richard Dawkins has responded and has said

    –> on “forensically” reconstructing the algorithm to do that, two main approaches are possible: explicit latching and implicit where the pop per gen, mut per letter rate and filter interact to at least some of the time give runs that ratchet. Both have been demonstrated and are legitimate readings on the evidence of 1986.

    –> on subsequent statements (and possibly the 1987 video] the latter is the — on balance of evidence — best explanation for the observed published runs and descriptions c 1986.

    http://scienceblogs.com/pharyn.....nt-1887052

    And

    http://www.youtube.com/watch?v=5sUQIpFajsg
    About 6:10 seconds in, watch the ‘Darwin’ algorithm home in on ‘METHINKS IT IS LIKE A WEASEL’. You will see (for instance at 6:16) that the program does not ‘latch’, because the W of weasel mutates and then comes back. It keeps winking on and off from W. Clearly no latching. However, as PZ and others have said, it really doesn’t make a lot of difference whether the program ‘latches’ or not. These people are so unbelievably stupid.

    I claim my trip to the Bahamas.

    Richard

    http://scienceblogs.com/pharyn.....nt-1886689

    Note that Richard says “the” program not “This version of Weasel (which is different to the version on TBW)”. Therefore according to Richard Dawkins there is only 1 version of Dawkins’ Weasel and it behaves as per the video (no latching).

    Will you now withdraw your opinion or continue to say that Richard Dawkins does not know how Richard Dawkins Weasel operates?

  190. The first Dawkins quote should have been

    Alas, I no longer have the original program. It seemed too trivial to be worth keeping. Obviously any half way decent programmer could knock it up in a trice.

    Fortunately, however, there is a film of the program in operation (see post #53) above, and you can clearly see from the film that there was no ‘latching’.

    http://scienceblogs.com/pharyn.....nt-1887052

  191. KariosFocus,
    I ask you one more time.

    If I have two programs.

    Once always outputs data similar to

    Generation 1: XXXYYYXXXZZZ
    Generation 2: XXXYYXXXYZZY

    The other always outputs data similar to

    Generation 1: XXXYYYXXXZZZ
    Generation 2: REJSJTHVHASG

    Would any reasonable person claim that they were in fact the same program producing similar outputs?

    No.

    Yet given two programs where the outputs are

    Generation 1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    Generation 10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    and
    Generation 1: XYBPFPBMCLPGFONJYWFKXPFOVMKDX
    Generation 2: XPJSQJMGPRYPONAIRJSGXZRWQJQBX

    you continue to claim that they are the same program!

    Please note the latter set of results were generated via WeaselWare here
    http://www.evoinfo.org/WeaselGUI.html
    So they are valid results. The previous generation 1 and 10 are obviously from TBW.

    Please explain Kariosfocus how these two outputs are in fact being generated by the same program?

  192. kf,
    anorther few thousand words ignoring my question, as expected. Too keep your evasion on display I will just repeat it: Which one of Atoms sehr algorithms is Weasel, which one the partitioned search? Are they the same?

    I will just briefly comment on a few of your points, there is too much noise in there to spend more time on it. Whenever you are ready to make a clear argument without all this obfuscation I will again be more exhaustive.

    implicit latching is an observed phenomenon, one that answers to CRD’s enthusiastic description and showcased printoffs.

    Of course it is: Nobody denies that evolution or Weasel are highly efficient searches. We are denying that that

  193. Indium:

    You first.

    I have repeatedly pointed out to you that most of your relevant queries were long since answered, starting with the always linked.

    So, your mantra on “ignored” is rising to the level of reite3rated false allegations, i.e slander.

    Kindly stop it. Point out where my answers are INADEQUATE on the merits — if you can — then you may go on from there.

    GEM of TKI

  194. kf,
    anorther few thousand words ignoring my question, as expected. Too keep your evasion on display I will just repeat it: Which one of Atoms sehr algorithms is Weasel, which one the partitioned search? Are they the same?

    I will just briefly comment on a few of your points, there is too much noise in there to spend more time on it. Whenever you are ready to make a clear argument without all this obfuscation I will again be more exhaustive.

    implicit latching is an observed phenomenon, one that answers to CRD’s enthusiastic description and showcased printoffs.

    Of course it is: Nobody denies that evolution or Weasel are highly efficient searches. We are denying that that Weasel protects correct letters from mutating.

    The primary fact is that Weasel is a confessed, targetted search

    Confessed targeted search? What are you talking about? It´s written with big letters in the book, there is nothing to confess at all! And this is not the question at hand anyway. The question is: Doe D+M misrepresent it?

    As such, Weasel c 1986 as presented is “fair game” for an analysis as-is, on the implications of the active information manifested by such cumulative, evidently ratcheted and latched search on mere proximity not relevant complex functionality.

    This alone is enough to amke any further argument with you rather unnecessary. Weasel is completely misrepresented in the paper by D+M. It´s not fair game to just plug in a different algorithm that happens to also keep correct letters (which Weasel sometimes even doesn´t do) and say your discussing Weasel. Also, please notice that D+M explicitly cite TBW and D announced on this blog that his paper criticizes Weasel and therefore even evolution. They give very specific results for the active info, which are plainly wrong for Weasel. Eq 22 is in no way consistent with Weasel (independend from latching). They are discussing a completely different algorithm, it is not fair game at all. That you consider this to be fair game speaks volume about a few things…

    how that latching is achieved is irrelevant to the point that active information is a key reason for the performance above unassisted random search, and to quantify the injected active information

    Quantifying active info for different searches is the main point of the paper by D+M. And yet the results for the partitioned search and Weasel are completely different which you would notice if you would just fire up Atoms software and check it. Or you can verify that Eq 22 is simply wrong for Weasel (latching or not latching, doesn´t matter) and therefore also the calculation is wrong. That does not imply that the active info concept can´t be applied to Weasel, I am sure it can be done! But it´s done wrong in the paper because Weasel simply is no partitioned search. Ask Joseph.
    kf, honestly, these things are now so clear to see for everyone that you are just damaging your reputation.

    The discussion and formulas in the paper are not correct for Weasel because quite simply Weasel is no partitioned search. Which is again a good point to repeat my question: Which of the Search Algorithms in Atoms suite is Weasel and which one the partitioned search? Maybe asking it two times in one post helps you to focus.
    Oh, and the bonus question: Do they seem to have the same amount of active info?

  195. Oh, sorry for the doulbe post.

  196. Kariosfocus

    So, your mantra on “ignored” is rising to the level of reite3rated false allegations, i.e slander.

    One could say the same about you.

    You have ignored Dawkins own comment on latching and Weasel.

    You have ignored comments that you are only seeing 0.047% of the total data and making assumptions based on that tiny fragment and applying the to the whole data set, as per comments #41, #78 and #149.

    You have ignored Indium’s simple question – “Which one of Atoms algorithms is Weasel, which one the partitioned search? Are they the same?”

    You have ignored my question #190, asked several times elsewhere and answered with a flurry of strawmen but no comment on the substance of the question itself.

    It is sadly evident from the above that we have much of straining at gnats while swallowing camels, as well as barking up wrong trees. Etc, etc.

    Perhaps you would be better served by addressing the issues on their merits rather then trying to accuse everyone who disagrees with you of slander.

  197. kf, you can I point you to where you ignore my question? You ignore it in all your thousands of words. Why not just answer it? Which algorithm from Atoms suite is Weasel, which one the partitioned search? Are they the same? Same active info? Same number of queries?

  198. Sorry again. First sentence should begin with “how”, not “you”.

  199. To Oatmeal’s excellent history of the whole affair at 181 , I would only add the following- the search shown in TBW cannot be a partitioned search, for the reasons Blue Lotus points out in 190 – the difference between generation 1 and generation 2. Something that D&M should be aware of.

    Kf has carefully avoided my post (164). He keeps saying “once latching occurs the D&M analysis applies”. This has been demonstrated to be false.

    Unfortunately (for him) he has now been backed into the position that Q is the total number of queries.

    kf@185:
    Where I do have what I think on further thought overnight is an error, is that I have taken Q to be number of generations at the first, in that context. Q is — on second thought — number of generations multiplied by size of generations.

    I insist that anyone who is having trouble following the math here, just go the
    http://www.evoinfo.org/Resourc.....elGUI.html
    and run a search for ‘Methinks it is like a weasel’. Then compare the Query Count for the Partitioned Search (about 98) with the Query Count for the “Proximity Reward Search” (which kf states (@163) is the Weasel algorithm)

    These were my runs (using G=50, MR=4%):

    Target: METHINKS IT IS LIKE A WEASEL
    Search Type: English Phrase
    Partitioned / Deterministic / Prox Reward
    1) 68 25 5850
    2) 85 26 4400
    3) 94 27 6800
    4) 156 27 6100
    5) 88 27 7800
    6) 78 23 11950
    7) 96 26 4800
    8) 90 27 9800
    9) 100 27 4000
    10) 93 26 5600
    11) 62 27 8700
    12) 127 27 4500
    13) 85 27 10150
    14) 115 27 5200
    15) 53 27 11850
    16) 90 27 6350
    17) 98 26 13950
    18) 83 26 5650
    19) 160 25 7700
    20) 121 27 5700

    So partitioned takes between 60 and 160 queries, but Weasel(50,4%) takes (using kf’s definitions throughout) between 4,000 and 13,000.
    These are “equivalent”?
    But don’t rely on anyone’s assertions – try it for yourself!
    Enjoy!

  200. BL:

    Your links above and quotes are, unfortunately, not helping us resolve the evident differences between the showcased runs of 1986, and the videotape of 1987.

    In short, the cites from Mr Dawkins raise — or miss — more questions than they answer. [And the ad hominems are unfortunately of a piece with his longstanding contempt for those who differ with him: ignorant, stupid, insane or wicked. Mr Dawkins: FYI, I have what seem to me to be some serious questions, and I am not simply setting out to smear and distort, I would like to have them resolved in a positive fashion. In that light I do not find off- the- cuff prejudice and dismissal civil; but instead to sound far too much like the incivility and regrettably ill-informed commentary that I and others, e.g, start here, find in your The God Delusion.]

    Some of the following has been raised several times but it will plainly bear repetition:

    1 –> the showcased runs of 1986, with gushing commentary on the wonderful power of CUMULATIVE selection, demonstrate that there is good reason to infer that the showcased runs did ratchet and latch their way to the target:

    ________________

    We may conveniently begin by inspecting the published o/p patterns circa 1986, thusly [being derived from Dawkins, R, The Blind Watchmaker , pp 48 ff, and New Scientist, 34, Sept. 25, 1986; p. 34 HT: Dembski, Truman]:

    1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL

    1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL

    [Cf my comments in the always linked app 7]
    _______________

    2 –> This pattern from 1986 — 200+ candidates that could revert in the samples if no latching is happening, but do not ever do so [consider on the import of the law of large numbers on this; i.e the simplest explanation that fits the facts is that the sample reflects the run of generational champions here . . . ] — cannot simply be dismissed by making an offhand comment on events of 1987. For, it is known separately that adjustment of parameters and/or different runs will produce cases that latch and cases that do not.

    3 –> In the case of the 1987 run, if the intent by Mr Dawkins is to say that he is showing the run of generational champions [a la 1986] — and that seems hard to avoid — then he is not explaining an apparent difference in showcased runs c 1986 and 1987, but distracting from it. (And Mr Dawkins is known to make significant use of misdirection and mischaracterisation in his public discussions, as the linked rebuttal to his The God Delusion documents.)

    4 –> If instead, CRD is showing the run of individual members of the population in the video, that these do not latch letters is a built in characteristic of the implicit latching case: it is the run of champions — the evidence that we are seeking to explain — that would show latching in the case where: [1] to a sufficiently high likelihood no-change members appear in the generation’s pop, [2] single step advances prevail otherwise. On this case, we will see latching of the run of champions as the current state will be locked in by [1] and advances if they happen will appear at [2] preserving the advances to date and occasionally adding to them. (And in some cases one run will latch and another will not on similar parameters. So, we are back at: wha tis being showcased in 1986 and in 1987, and how represenattive of the runs and population is that.)

    5 –> Not to mention, how does the behaviour ofthe population fit with the gushing claims from BW that accompany the above runs:

    ____________

    >> It [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer [indirectly, the programmer!] examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection [i.e. "more than a million million million times as long as the universe has so far existed" -- this is where CRD admits that active information has played a key role in the speedup] . . . >>
    _________________

    6 –> If double changes etc appear with sufficient frequency, we will see another demonstrated characteristic: substitutions where one letter advances, and another retreats — which then tend to run across decadal generation boundaries. [this would be in either a quasi-latched or an unlatched case.]

    7 –> In the showcased 1986 runs, it took 40+ and 60+ generations to hit target, so that no-advance won the generation contests about half the time, i.e. we have separate reason to see that we may well be in the implicit latching regime described.

    8 –> And, if the showcased runs were unrepresetnative of he performance of Weasel c 1986, then CRD has some expalining to do on his gushign comments about cumulative selection.

    9 –> Lastly, he seems to be suggestig that he weawsels out there more or less capture the patterns of behaviour. In this case, then explict latching and implicit latchigtn are legitimate interpretations, and ont he evidence that he presented he4 has showcased implicitly latched runs c 1986, and either internal members of po per gen in 18987 or a case taht is distinctly dfifferent formt he 1986 runs.

    10 –> Or else, if the showcased 1986 runs did not ratchet to target, then his published excerpts were misleading – and that in a context that he admitted was in the broader sense “misleading.”

    GEM of TKI

    PS: BL, 190: You are missing the point, and are reading INTO the remarks in the paper something that is not drawn out of it. This happens fairly frequently, so we do have to watch out for it.

    Try reading on a different “scenario,” and see if this helps you see where I am coming from: “On p. 1055 M & D presented a didactic example of what partitoning of a search means, not a real world output of a program or illustration of an algorithm’s typical output in one step.”

    This, I have pointed out step by step from 161 above on, as a more credible explanation. In short, I see from my angle that on inference to best explanation, M & D are NOT presenting an algorithm or program or output from a run, but they are explaining a concept, then they go on to use the evident ratcheting as given above for Weasel 1986, to show its mathematical consequences.

    Runs from 1987 are irrelevant to the 1986 result which do show no reversions among the run of champions, in a sufficiently large sample that with the gushing commentary on cumulative selection, one may reasonably conclude that the program runs showcased did latch or ratchet, manifesting partitioning explicitly or — more likely on balance of evidence and testimony — implicitly achieved.

    That is the M & D Analysis is about what searches that show cumulative, ratcheted, latching selection do, and is thought to be relevant to the 1986 Weasel runs as showcased for reasons of the size of sample [as measured in letters] and the lack of reversions therein. Such ratcheting can be achieved by explicit or implicit latching effects, and on balance of evidence the later is most likely.

    In any case the underlying analysis is relevant and applicable as CRD’s commentary in BW reveals — inadvertently — that the active information supplied by use of a preloaded target and a proximity hotter-colder metric and filter, makes the program outperform random walks by a wide margin.

  201. Your links above and quotes are, unfortunately, not helping us resolve the evident differences between the showcased runs of 1986, and the videotape of 1987.
    The differences can be easily explained by the size of the population used in both examples:
    Using a mutations probability of 4%, a population of 10 takes 1305 generations on average, a population of 100 takes 78 generations.
    Obviously, Dawkins wanted to have the program running for the length of his talk, so he chose a smaller population than for the book. I’m sure that Dawkins would answer along these lines – if he was asked.

  202. BTW, these numbers are calculable, you don’t have to take my word for them…

  203. kf, you are so fixated on the latching stuff and the imagined differences between 1986 and 1987 it is honestlyn amazing. And of course you still avoid my questions! Hilarious!

    You are more and more retreating to the strange position that the algorithm that D+M describe is not really Weasel (admitting what we say all the time) but is still relevant even if the math is completely incorrect. Could you elaborate? How much active info does the real Weasel then have? Why don´t D+M discuss Weasel when say reference it and boast about their critic on this website?

    So, have fun discussing this with Dr. Dembski, who seems to think that he criticized Weasel and not something else.

  204. 204

    @kairosfocus, #185

    By all means, the behavior you call latching exists. You have twice demonstrated such and ignored the question. It appears the definition of latching/ratcheting in effect (explicit, implicit, or quasi-) is that if the search moves toward the target, then “it must be latching because it looks like latching”. I suggested a more formal mathematical definition, and I am unaware of any other definition.

    I have to conclude that the concept of latching and ratcheting is arbitrary, or that it is a property of all search algorithms other than blind random search. Either way, it seems to be a useless concept.

  205. –kf,
    I just wanted to add my voice to the choir:

    Which algorithm from Atoms suite corresponds to Weasel and which one corresponds tpo the Partitioned Search discussed by D+M?

  206. Tomato Addict:

    I have to conclude that the concept of latching and ratcheting is arbitrary, or that it is a property of all search algorithms other than blind random search. Either way, it seems to be a useless concept.

    I think KF has even tried to imply that a blind random search has a latching mechanism here:

    One of the peculiarities of Weasel algors, is that they halt when they hit home; of course halting being a key property of algorithms. As a result, if they hit home before a generation number G, they do not get to G. Thus, if Q means number of mutants to date, then if size of generation is S, Q = G*S.

    Immediately, if a run completes [all L letters correct] at gen G, it cannot have been complete before G.

    So, the paper’s p.1055 discussion would on this reading of Q would be of a ratcheted run that shows a march of champions with latching up to G, when it halts: completion AT G. (In an explicitly latched Weasel this would be automatic, in a version that on being tuned and giving a good run latches — as observed [our first swallowed camel . . . ] — this implies that when metric falls to distance to target = 0, there is a latching action imposed.)

    KF is trying to make an art out of semantic mud wrestling. He is claiming that if an algorithm has a halting condition then this is a latching mechanism and because it is assumed that both Dawkins and D&M’s algorithms are assumed to halt when they find the target, they both contain a latching mechanism. KF presumably doesn’t regard the fact that this latching has no affect on the search as important.

    Dawkins also doesn’t specify a halting condition and one is not actually required, although it would seem daft not to write one in. You can leave WEASEL running after it has found the target and it will continue to produce new generations, and the fittest will sometimes show incorrect letters. This becomes vital if you change the target to a new phrase because WEASEL will start to converge on this new target.

    Contrast this with Dembski and Mark’s algorithm. They appear to specify a halting condition “The search for these letters is over” but it is slightly ambiguous. I realise that you could interpret and code it either way as follows:

    1

  207. (Hmm, for some reason it just posted my comment for me before I finished – here is the rest)

    1 You code it so that there is a running list of incorrect letters. You work though this list on each iteration of the software and randomise letters on it. When the list is zero the program implicitly halts (or loops for ever doing nothing)

    2 With each programme loop you check each letter, if it matches you do nothing, if it doesn’t you randomise it.

    Option 2 is simpler but functionally equivalent as far as I can see EXCEPT that option two will re-converge on a new target if one is set. The latching mechanism in option 1 is permanent but in option 2 it is only permanent (i.e. non reverting) if the target does not move. I think both could be argued as legitimate interpretations?

    Of course there is still an explicit mechanism required for D&M’s compared to Dawkins algorithms.

    The issue over halting conditions is a rather sad but amusing attempt to stretch the idea of latching behaviour even further – it would apply to any algorithm that can achieve its goal and renders the idea of latching, in the context of D and M’s representation of WEASEL, meaningless.

    When looked at clearly – without KF’s will-full attempts at obfuscation, his handy portable goal posts and the bulldozer he is using to try and re-shape the playing field – there is no way you can follow both algorithm descriptions and come up with the same code.

    Onlookers may also have noted how he laces all his comments with poisonous accusations of dishonesty. An upstanding example of civil discourse for sure!

  208. KF,

    I think after reading the comments at Pharyngula, virtually everyone will agree that Dawkins’ WEASEL did not use partitioned search.

    That’s really the relevant point here, not whether the algorithm involved quasi or implicit latching, concepts which don’t appear in the paper and which D&M don’t discuss.

  209. Its worth repeating this:

    D&M’s process:

    With each programme loop you check each letter against the target, if it matches you do nothing, if it doesn’t you pick a letter at random to replace it.

    Repeat.

    Dawkins method:

    With each programme loop copy each letter of the previous winning phrase, with each letter copied having a probability (P) of being randomly replaced. Now add up the number of complete letters to get the fitness score. Perform this G times (where G is the number of generations). Now look through the list of scores and pick the highest, or any one of the highest if there are more than one.

    Repeat.

    So should we consider these two processes to be the same? They can’t be written the same way as code, they don’t function the same way and they don’t produce the same results.

    Can they be considered the same for D&M’s purposes (according to KF). Well I don’t see how – the question about the amount of active info is very pertinent here – but this is also irrelevant to the main topic under debate, one which it is easy to loose sight of what with KF’s army of oily burning sixty foot straw men marching across these pages. D&M describe a different process than Dawkins does, the differences are not trivial, particularly to anyone familiar to the topic of search algorithms. Because of this their reference to Dawkins work is incorrect and inappropriate; it should be corrected – and this will have no impact, as far as I can see, on the content of their paper.

    The surreal and farcical attempts to avoid this quite simple issue begs the question – is this really about search algorithms at all or is it about poking Dawkins with a stick.

  210. BillB, as far as I can see only kf continues with this marathon of distractions. I am quite sure that Dr. Dembski will of course correct his misrepresentatiojn soon, it´s easy enough! For a man with his integrity it will only take a few days or 1-2 weeks to prepare a correction. I would bet a (very small) amount of money that he has so far not been made aware of these problems.

    So, may I ask again: Instead of waiting for Dawkins to show up here, which is very unlikely, why doesn´t Dr. Dembski explain the issue on his own blog? Can somebody ask him for a clarification? On the other hand he closed comments on the thread where he announced the paper. Thanks Clive and O´Leary for opening new ones, btw!

  211. Oops. Sorry, I didn’t realize before that kf is actually suffering from a pathology. I’m astonished at the stamina of those who are arguing with him, but somewhat perplexed as to why they bother. Is someone who is so hung up up on the specifics of a program written 20+ years ago, and whose algorithm has been shown time and time again to exhibit just the behavior that was claimed for it, really worth arguing with?

    The really funny thing about all this is that RD’s claims for the program were so tiny, and his acknowledgment of its limitations so clear, you really have to sympathize with someone whom it causes to spill so much virtual ink.

    Good luck with the debate, all!

    (Yes, I don’t mention the Dembski algorithm because it is, of course, a huge irrelevancy.)

  212. I’ve just been observing with a mix of amusement and astonishment. It is a vary minor but clear issue, these are two different algorithms, Dembski and Marks made a mistake in their citation, they should issue a correction, Kariosfocus can stop making a mockery of reason (and ID), everyone can move on.

  213. nephmon,
    observing how kf tries to defend some truly obvious errors with more and more distractions/obfuscations provides a certain amount of amusement to some people.

  214. Kairosfocus,

    In short, the cites from Mr Dawkins raise — or miss — more questions than they answer. [And the ad hominems are unfortunately of a piece with his longstanding contempt for those who differ with him: ignorant, stupid, insane or wicked. Mr Dawkins: FYI, I have what seem to me to be some serious questions, and I am not simply setting out to smear and distort, I would like to have them resolved in a positive fashion. In that light I do not find off- the- cuff prejudice and dismissal civil; but instead to sound far too much like the incivility and regrettably ill-informed commentary that I and others, e.g, start here, find in your The God Delusion.

    I suppose your words are heartfelt, but wouldn’t it have been easier and more conducive to the matter at hand, once and for all to offer a couple of words just to answer that simple question:

    I ask again: Which algorithm from Atoms suite corresponds to Weasel and which one corresponds tpo the Partitioned Search discussed by D+M?

    or

    Which of Atoms algorithms is the partitioned search and which one Weasel?

    Since you have made a lot of references to Atom’s program:

    Nor is this theory, there are actual runs that do that. (HT: Atom and EIL.)

    using replication of results as a good cross-check, e.g through Atom’s adjustable Weasel, here.

    j] As already noted and linked, these patterns have been demonstrated through actual runs of Atom’s adjustable Weasel, from EIL

    I think it would be a good idea to answer the question, or at least tell us why you don’t consider it relevant? I believe a lot of people are interested but I am afraid your performance so far has not convinced many of them.

  215. To be honest, Cabal, the answers to these questions will probably no longer be of much interest now that kf has more or less admitted that D+M discuss something that is NOT Weasel. I bet he will still avoid them anyway, otherwise he will have to contradict himself even more.

    In fact, all questions have now more or less been answered:
    - the explicit/implicit latching obfuscation has been exposed (about 100 times now)
    - it is obvious that Dembski and Marks don´t use a proper Weasel and therefore misrepresent Dawkins

    The only one left on the sinking ship is kf, so who cares except for people interested in the argument regarding design?

  216. With computers being binary devices, how can ‘implicit latching’ be implemented?

    To me, implicit latching have a ring like ‘implicitly pregnant’?

  217. kairosfocus:

    In short, more word twisting and strawmanising.

    No, it’s a simple statement of uncontroversial fact. The EIL page presents math (the same math as the IEEE paper) that purportedly apply’s to Dawkins’ algorithm. The simple fact is that it does not apply to Dawkins’ algorithm. This is made abundantly clear by the fact that the math does not take into account population size or mutation rate. But if you still don’t believe it, run the numbers yourself, as I did above. There is no controversy here — the numbers don’t lie.

  218. Cabal: in this case, “implicitly” simple means “having the appearance of”. If you look at the output of an unlatched weasel program using a suitable offspring population size and mutation probability, you will see that once a letter has matched the target, it will never be corrupted again in the next generation, giving the appearance that it’s latched.

    Of course, amongst the 200 (say) candidate offspring, many of them WILL have a corruption of already correct positions, but these ones never (or with a vanishingly small p, anyway) get selected to go forward to the next generation.

    If you make the offspring population small enough (or the chance of mutation high enough), then you WILL see letters flipping between correct and incorrect, and indeed it will never converge on the target string.

    I’m sure someone will say “Aha! So you have to TUNE the values to make it work!” to which I would reply, evolution is quite capable of tuning such meta properties of the process itself.

  219. 219

    BillB writes> I think KF has even tried to imply that a blind random search has a latching mechanism here:

    AND

    KF writes> One of the peculiarities of Weasel algors, is that they halt when they hit home; of course halting being a key property of algorithms.

    I think BillB is correct: This seems to be saying that any algorithm that halts is latching, and that Weasel is peculiar for doing so?

    Therefore even a blind random walk that happens to find the target – and halts – is latching.

    I state as a given that halting is a universally accepted property of good coding practice. However, since good practice is not requirement, any search in an infinite loop might be considered non-latching. If halting is latching, I could be forced to admit this meets my request (in #146) for an example of a non-latching search algorithm. It would be a really stupid non-useful example though.

    Usefulness aside, by this definition I can now claim that all algorithms that halt, or might halt, exhibit latching. The very concept of latching and ratcheting is now even less meaningful than before.

    @KF: You wrote a lot, and I am willing to give you the benefit of the doubt and allow the quote above is perhaps taken out of context. I don’t think it matters. The point I would repeat is that latching and ratcheting are either undefined, arbitrarily defined, or so broadly defined (pick one), as to be useless.

  220. 220

    Well, here’s one that I wrote up. Non-latching, highly configurable, and doesn’t require the start string to be 28 characters (it can be any length). You can furthermore choose penalty weighting, etc.

    Should that work, I’d go with Dawkin’s book. In any case, the program is really quite simple, and Panda’s Thumb had a nice breakdown of the convergence times of latching and non-latching programs (though all with 28 character starting strings).

    Direct program link here.

  221. Mrs O’Leary (and onlookers):

    Let us first draw attention to the issue for this thread: absent someone out there having a copy that is currently unknown, no copy of Weasel c 1986 code will be forthcoming.

    It therefore remains to correct a few mis-impressions and to underscore the real central issue and achievement of the recent IEEE paper (and its stable-mates).

    For, the clutch of papers introduce an extension to the achievements of design theory: active information as an explanatory factor for the superior performance of intelligent search over blind, random search in large configuration spaces. And, we may again underscore that Mr Dawkins, in 1986, inadvertently pointed the way to that conclusion when he developed Weasel as a targetted, proximity increment rewarding search for a preloaded target:

    ____________

    >> [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed . . . .

    Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no long-term goal . . . In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success. [TBW, Ch 3, as cited by Wikipedia, various emphases added] >>

    ______________

    1 –> Now, clearly, Dawkins accounts for the advantages of his “cumulative selection” that rewards mere increments in proximity to “a distant ideal target” by “nonsense phrases” over the “single step selection” — i.e. random mutation that has to achieve significant function before it can hill-climb — he would dismiss by the active information contained in the target, the comparison to target and reward of hotter as opposed to colder NON-FUNCTIONAL phrases.

    2 –> So, the core point of the current series of papers was inadvertently acknowledged from 1986. By Mr Dawkins.

    3 –> Q: So, why has there been a debate over a plainly secondary (and often simply contentious and distractive) issue — latching and/or ratcheting — since December last?

    __________

    ANS: i] Of course, the answer has long been accessible one click away, from App 7, the always linked.

    ii] And, yes, there is a bit of Darwinist revisionism of history at work here, projectively shifting the locus of “obsession” to those who have pointed to the reason why explicit and implicit latching are valid interpretations of the description and showcased printoffs from Weasel c 1986.

    iii] In the main, this is because the issue was raised again and again and again by Darwinist objectors to those who pointed to the evident ratcheting action published by Dawkins in 1986; objectors who to often insist on mischaracterisations and resist the most reasonable and simple corrections.

    iv] Presumably, they raised it in the main because it is a point where they think they can discredit those who they object to, while focussing on what they want to highlight rather than the more embarrassing — for them — details of Mr Dawkins’ statements as cited above.

    v] Unfortunately for them, they thereby show for the discerning reader several of the standard Darwinist rhetorical tactics of misdirection, mischaracterisation (of both arguments and persons) and dismissal.

    vi] For instance, they are unwilling to acknowledge that the plain fact is that in the published, showcased — presumably “good” but representative — print runs of 1986, the excerpted runs of champions show as a matter of fact that in 200+ cases of letters that if reversions from correct were frequent we would see a few reversions, we see NONE. (Cf. on the law of large numbers and observability of low-probability phenomena here in App 7. [Do we not find it interesting how adverse comments are routinely being advanced by the Darwinists without seeking to fairly represent those being criticised.])

    vii] Equally, they do not wish to acknowledge that in his gushing comments on the prowess of Weasel’s cumulative selection in BW, CRD used a term that normally means: “Increasing or enlarging by successive addition,” which when multiplied by the highlighted runs strongly supports the conclusion that at minimum, “good” runs of weasel produced lines of generational champions that routinely behaved like the published excerpts.

    viii] So, CRD has the dilemma of either using misleading examples/excerpts, or using misleading words. (And that in a context of acknowledging that the is being in key parts misleading — Weasel as described is intelligently designed, targetted search, not a good stand-in for chance variation and natural selection based on differential FUNCTIONALITY.)

    ix] Similarly, there has been a campaign to discredit the concept of ratcheting or of latching. In fact these are quite simple: based on what we see in the 1986 runs of champions, when Weasel is working “right” it will hold on to correct letters, and it will add more until the target is achieved, generation by generation. As in what seems to be clearly going on in the 1986 runs — at least if we are unprepared to swallow the “don’t believe yer lyin’ eyes” rhetoric.

    x] So far, we have highlighted the pattern observable/ supported by the showcased runs c 1986 and the commentary on them. The question is where did these come from?

    xi] One obvious possibility is explicit latching, and this is a legitimate interpretation of the information c. 1986. However, on further commentary and claims c 2000 and currently from Dawkins and proxies, the other possibility seems to be more likely: IMPLICIT LATCHING; as is discussed in the App 7 and in earlier UD threads. (The mechanism that Darwinists seem to want to either dismiss as unreal or accept as trivial.)

    xii] But in fact, since CRD has in effect accepted that Weasel type algorithms as implemented in recent years are more or less typical of what his program did, we can rely on the demonstrated and long since publicly posted fact of implicit latching shown by Atom’s adjustable weasel. (I’ll bet some onlookers would not realise that such is demonstrated fact from the objections above and elsewhere!)

    xiii] Thus, we can see that indeed under certain conditions where the population size per generation, the mutation rate per letter and the filter work together right, the sequence of generation champions on closest yet approach to target will show latching and ratcheting. (How desperate are some objectors to dismiss the observed fact as non-existent or poorly defined!)

    xiv] How this likely happens: under not too hard to achieve conditions (enough pop and a reasonably low mut rate)the mutant population form a seed will almost certainly contain at least one unchanged member — cf calculation and explanation in the App 7 on this.

    xv] That means that practically, progress to date on proximity will be preserved, given the stipulation on the filter. And, if in addition, single step advances are favoured otherwise because the mut rate is fairly low [so that 1 mutation per child phrase is typical], then mutations that affectt he correct letters will tend to be retreats, and will be eliminated by the filter.

    xvi] Most mutations of non-correct letters will make little or no difference to the proximity too (or if they hit a correct letter they will most likely revert it to incorrect for that member of the pop). But when a newly correct letter arises and the presently correct ones are undisturbed for a member of a generation, we have a one-letter distance increment in proximity. if such a member is present, it will be picked by the filter in the normal case. [Obserfve how int eh Weasel 1986 runs as showcased, we saw 40+ and 60+ gens to target for "good" runs. That is no-change won out about half the time, and single step increments in proximity dominated the rest.]

    xvii] Of course, where mutation rate or population size is high enough, we will see occasional cases where double mutations pop up which may give a two-letter advance, or may substitute one correct letter for another: the latter marking a LOSS of latching behaviour.

    xviii] On the other end, if the pop size per gen is too small, not enough members of population will be present to have a predictable pattern within the generation, so reversions may win, and latching vanishes again. (Hence the discussion on tuning or matching of pop size, mut rate and filter. The filter, of course, can also affect outcomes, as is mentioned in the App 7. As Apollos inadvertently demonstrated some months back, this can sometimes have a dramatic effect.)

    xix] If reversions are rare, we see near-latching or as I have termed it quasi-latching with an occasionally slipping ratcheting action.

    xx] Indeed, given that the above are probabilistic phenomena, do enough runs and you will see reversions in cases where latching “often” turns up. For a probabilistic barrier is not an absolute barrier.

    xxi] That brings up the 1987 videotaped runs. Most likely, they showcase a detuned run, which does not latch implicitly, and the onscreen reversions may reflect that. (It is also possible that the video is highlighting the members of the population, which are not the same as the run of generational champions published in the 1986 printoffs. The two are not mutually exclusive.)

    xxii] Beyond that, we may see behaviour that does not in any wise resemble latching, i.e cases with a rather high mutation rate will find it hard to close the deal, and maybe in some cases will never hit home to the target.

    _________

    4 –> Now, none of the above is really new, having been put up several times — including in this thread. Not to mention, it is presented in the always linked app 7. Why then is it apparently so hard for Darwinists to see what should be obvious?

    5 –> Partly, because it does not fit with what they expect to see. (It is hard to see what is really there when that does not fit with what you expect to see.)

    6 –> For instance, just above we see TA @ 219: The point I would repeat is that latching and ratcheting are either undefined, arbitrarily defined, or so broadly defined (pick one), as to be useless.

    7 –> Compare that ill-informed, counter-factual statement with the facts as again outlined. How could a reasonably informed person not see that here is a sufficiently precise definition, with publicly accessible demonstrations [starting with the showcased Weasel printooff excerpts of 1986]? And counter-examples that show contrasting cases?

    ANS: because the actual facts cut across the expectations. [Starting with "don't believe yer lyin' eyes" on what Weasel 1986 credibly did.]

    8 –> In that context, it is easy to see as well why a focus on an imaginary flaw can distract from the actual outright acknowledgments in BW of:

    [1] use of artificial selection,

    [2] resulting material dis-analogy of this computer simulation to chance variation and natural selection,

    [3] the further resulting fundamentally “misleading” nature of the Weasel icon of evolution,

    [4] the actual reason for improvement in performance over blind search: active information in the form of a preset, embedded target and a hotter-colder beacon that draws in non-functional “nonsense phrases” until they hit home in a few dozen generations if the program is set up right.

    [5] the distraction from and dismissal of the need to de novo originate complex functional information through chance variation before hill-climbing/ warmer-colder algorithms etc can be legitimately employed.

    9 –> And this last cluster extends directly to the more modern and more sophisticated Genetic Algorithms. GA’s may reasonably mimic certain aspects of micro-evolution, but hey do not credibly account for the origin of complex information based functionality in the absence of intelligent action and the associated injection of active information.

    10 –> And, that is a fatal defect.

    GEM of TKI

    PS: BillB of course — as is sadly usual — manges to excerpt out of context and mischaracterise. The context for my remark on halting was that because of halting, Weasel type algors will lock up as they hit home. that means that when we talk about probabilities of getting home AT gen x, we are talking about just that — we would not get to to gen X if there had been an earlier hitting of the target.

  222. PPS: TH, you can see an implicitly latched run of Atom’s adjustable Weasel hit home in 31 gens here.

    I reproduce, FYI, as it seems hitting on a link is not popular:

    ___________________

    RUN B, 500 pop/gen, 4% per letter mut rate:

    1. MEL LSI YHXMAJLMDGMVKTSKGW
    2. MEL LSI YHXIAJLMDNMVKTSKGW
    3. MEL LSI YHXISJLMDNMJKTSKGW
    4. MEL LSI YHXISJLMDN JKTSKGW
    5. MEL LNI YHXISJLDDN JKTSKGW
    6. MEL LNI YHXISJLDDN JKTEKGW
    7. MEL LNB BHXISJLDDN JKTEKGE
    8. MEL LNB BHXISJLIDN JKTEKGE
    9. MEL LNB BHXISJLIDN JKTEKSE
    10. MEL LNB BHXISJLIDN JKTEKSEL
    11. MEL LNK BHXISJLIDN JKTEKSEL
    12. MEL LNK BHXIS LIDN JKTEKSEL
    13. MET LNKV BHXIS LIDN JKTEKSEL
    14. MET LNKV BHXIS LIDN AKTEKSEL
    15. MET LNKV BHXIS LIDE AKFEKSEL
    16. MET LNKV BHXIS LIKE AKFEKSEL
    17. MET LNKS BHXIS LIKE AKFEKSEL
    18. MET LNKS BH IS LIKE AKFEKSEL
    19. MET LNKS BH IS LIKE AKFEKSEL
    20. MET LNKS BH IS LIKE AKWEKSEL
    21. MET INKS BH IS LIKE AKWEKSEL
    22. MET INKS BH IS LIKE AKWEKSEL
    23. MET INKS BH IS LIKE AKWEKSEL
    24. MET INKS IH IS LIKE AKWEKSEL
    25. MET INKS IH IS LIKE A WEKSEL
    26. MET INKS IH IS LIKE A WEASEL
    27. MET INKS IH IS LIKE A WEASEL
    28. METHINKS IH IS LIKE A WEASEL
    29. METHINKS IH IS LIKE A WEASEL
    30. METHINKS IH IS LIKE A WEASEL
    31. METHINKS IT IS LIKE A WEASEL
    _________________

    And this one hit home in 21 gens:

    _______________

    Case D: 999/gen [maxed out], 8%:

    ________________

    1. MMCJXLTPPCNATTMLKDXOBDKMBJQX
    2. MMCJXL PPCNATT LKDXOBDKMAJQX
    3. MMCJXL PPCNATT LKDXOB KMAJUX
    4. MECJXL PPCLATT LIDXOB KMAJUX
    5. MECJXL PPWPOVS LIDXOB WMAJUX
    6. MECLXL PPWPOVS LIDXOY WMAJUL
    7. MECLXL SPWPOVS LIDXOY WMAJUL
    8. MECLXL SJWPOIS LITXOY WMAJUL
    9. MECLXL SJWP IS LIZXOY WTASUL
    10. MECLXL S WP IS LIZAOY WTASUL
    11. MECLXL S IP IS LIZAOY WTASEL
    12. MECLXL S IT IS LIZAOY WTASEL
    13. MECLXL S IT IS LIKNOY WTASEL
    14. MECLXL S IT IS LIKEOY WTASEL
    15. MECHXL S IT IS LIKE Y WUASEL
    16. METHXZ S IT IS LIKE Y WUASEL
    17. METHXZ S IT IS LIKE A WUASEL
    18. METHKN S IT IS LIKE A WUASEL
    19. METHKN S IT IS LIKE A WEASEL
    20. METHIN S IT IS LIKE A WEASEL
    21. METHINKS IT IS LIKE A WEASEL
    __________________

    Here we see speeding up of run to the target.

  223. PPS: On a subtlety: when mutation occurs, the same letter is a candidate, so 1 in 27 times, a mutation will go back to being itself. As an effect of that, 1 in 27 times on average, when a correct letter “mutates,” it goes back to being itself. That should not be overlooked in analysis.

  224. I’ve often wonder if the fact that the weasel program is performing directed a search at “a distant goal” is as troublesome as even RD states.

    If you think of the phrase “methinks it is a weasel” as representing the environment in which the mutated, generated phrases are “living”, then what the program is doing is optimizing the progeny of the random seed phrase for fitness in that environment.

    Of course, there are many simplifications involved here: the “environment” happens to also be a specific value of the “genome” that’s evolving; there is no analogue of a phenotype resulting from simple genotype that’s being modeled (and on which selection would operate in reality); and the “environment” never varies. (This last point is easily addressed by also mutating the target phrase across generations, so that the program will now be chasing a moving target, which is closer to the idea of organisms adapting to slow-changing environments. Of course in this case, it’s unlikely the simulation would halt, just like evolution.)

    There are many other enhancements that could be made to the program to better model real-world evolution, and I’m sure many such simulations exist. But I still think that as a very simple-to-understand illustration of the vast difference between random mutation and the selection of random mutations according to some selective pressure, it holds up pretty well.

  225. kf@222: can you explain why you’re reproducing that? I think almost everyone here has written an implementation of the weasel algorithm and has observed the fact that with many progeny to choose from in each generation, a letter that is already correct is not going to change in the next generation (unless p(mutation) is extremely high).

    So what are you revealing by listing a result that’s already very well known? Is it that you’re trying to prove that RD’s original program would have behaved just as he claimed in the book without having to fix letters in place once they’d matched, and therefore we don’t need to see the source code?

    Thanks anyway, but I think we know that already.

  226. –kf
    sorry, I couldn’t spot where in your variably emphasized and enumerated post you answered the question:

    Which algorithm from Atoms suite corresponds to Weasel and which one corresponds tpo the Partitioned Search discussed by D+M?

    And for your subtlety:

    when mutation occurs, the same letter is a candidate, so 1 in 27 times, a mutation will go back to being itself.

    Why? That’s just a question of implementation. Doing it this way, a possibility of 4% of change for a letter would translate into a de-facto-mutation rate of 3.85% – but you can also achieve a mutation rate of 4% if you chose uniformly only from the other 26 symbols.
    For practical purposes, it’s not much of a difference…

  227. kf, everybody here has understood the latching issue. The main point is that we all agree that there is no proof or evidence that explicit latching is involved. This was the original question of this thread and it has been solved a long time ago. The programm DOES let the characters vary, the subsequent filtering eliminates bad mutations most of the time. Your letter counting (“as a matter of fact that in 200+ cases of letters that if reversions from correct were frequent”) is of course wrong because you should a) count only correct letters and b) take into acount that you only see every 10th generation so that wrong letters have a good chance to be restored anyway.
    How often do we have to go through this?

    The discussion has moved on. It has now been shown that this is by far not the only misrepresentation in the D+M paper. In fact they use a completely different algorithm while referencing Weasel. This is most easily demonstrated by checking Eq 22 which is incorrect for Weasel. Even Joseph has acknowledged this.

    And finally, you continue to evade my questions which in turn continues to amuse me. I will repeat them later for your convenience!

  228. nephmon – you and I may already understand how a program that has no latching mechanism may still display latching behavior, but it is nice of kf to explain it to this audience, even if he is a bit long-winded about it.
    Let us remind ourselves that kfocus has defined Q as

    kf @185
    Q is — on second thought — number of generations multiplied by size of generations

    And he has told us (@163) that Weasel is the same as the “Proximity Reward” search (this, at least, is true).

    I am surprised that kf (@222) would then showcase Weasel runs with Q = 999 x 21 and 500 x 31

    As shown in the D&M paper, Q for a Partitioned Search has a median of 98, and should rarely go above 160.
    But according to kf, his didactic examples of Weasel runs have values of Q of 20,979 and 15,500.

    And he still wants to argue that D&M’s use of eqn22 to describe Weasel is accurate.

  229. NM:

    Plainly, you represent the “it doesn’t matter . . . ” faction!

    Again: the primary issue is that Weasel’s superiority over “lucky noise” comes from its active information, manifested in targetted, proximity rewarding search that picks and promotes non-functioning “nonsense phrases.” (This was actually inadvertently acknowledged and/or implied by CRD in BW.)

    The secondary debates over Weasel and explicit or implicit latching have to do with [a] how the results showcased in 1986 were best explained, [b] responses to attempts to dismiss that. Latterly [c] to the claim that here is a radical divergence between what Weasel 1986 did and the description ion Marks and Dembski’s IEEE paper that the showcased results reflect partitioning due to ratcheting action [which enfolds latching of correct letters].

    Unfortunately, we have also had to deal with a lot of Darwinist rhetorical games that drag distractive red herrings, lead off to strawman misrepresentations soaked in ad hominem mischaracterisations, which are then ignited to cloud, confuse, poison and polarise the atmosphere. (Apart from this factor, we probably would not have had several threads at UD since about March running over 1,000 comments on a plainly SECONDARY matter. There are threads where I have actually been rebuked for pointing out the primary issue, as being distractive from the “main” point!)

    I trust this sets the matter in clear enough context.

    GEM of TKI

    PS: Lest we forget, here arte the showcased runs of Weasel from 1986:

    _________________

    We may conveniently begin by inspecting the published o/p patterns circa 1986, thusly [being derived from Dawkins, R, The Blind Watchmaker , pp 48 ff, and New Scientist, 34, Sept. 25, 1986; p. 34 HT: Dembski, Truman]:

    1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL

    1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL
    _________________

    These are runs of generational champions, used to seed the next successive generation. For over 200 cases of letters that go correct, there are no reversions thereafter that are seen in the sample — and since we can easily see how persistent incorrect letters often are [E.g. cf the initially incorrect W, C Z and M in the first run and the Y, P , F and Q in the second] — this strongly argues that there are none; especially given the gushing description of “cumulative selection” in BW.

  230. KF

    Yet again you need to be reminded of the basis for this debate, and O’Leary’s question.

    The issue is whether Dembski and Marks describe the same algorithm as Dawkins in the section of their paper where they reference The Blind Watchmaker. It is a question of good scholarship, of correcting your errors when they are pointed out.

    The issue of WEASEL’s biological plausibility, of whether it explains how life began, is totally irrelevant to this issue of scholarship – WEASEL could be a total failure at whatever Dawkins was trying to achieve, but it is still wrong to misrepresent it in a peer reviewed paper.

    Please can you try and stay on topic. If you want to discuss the interesting and worthwhile question of how WEASEL applies to biology, or the technicalities of Dembski and Marks paper then I’m sure Clive would oblige with a separate thread. The question we are trying to get a clear answer on is purely about why Dembski and Marks cite the WEASEL algorithm in The Blind Watchmaker, but then describe a substantially different algorithm.

    You are jumping backwards through oily hoops to try and make out that the differences between these two clearly different things don’t amount to anything. It is both tragic, and very entertaining.

    Moving on…

    When you said this:

    this implies that when metric falls to distance to target = 0, there is a latching action imposed.

    You appeared to be trying to claim halting as a latching mechanism relevant to the debate on latching mechanisms, I’m glad that this was just poor communication on your part, but why mention halting with reference to latching at all? – it seems irrelevant to the debate but on closer inspection it highlights the differences between WEASEL and a partitioned search.

    Without an explicit stop condition for the software Dembski and Marks algorithm will stop searching when it hits the target and loop forever doing nothing. WEASEL will continue to produce generations, each with mutated members and, depending on mutation rates and population sizes, the winning phrase will continue to show occasional reversions even after the target is found. So when you say this:

    Weasel type algors will lock up as they hit home.

    You are in error.

    I also agree with nephmon about your comment at 222 – what was the point, you are just demonstrating what we already know – that a latching mechanism, an explicit piece of code to lock correct letters out of the search, is not required. You seem to have a blind spot about this issue and the way it impacts the two algorithms, I’ll try and explain (again):

    Dembski and Marks describe a series of searches for individual letters – each letter is ranomised and checked against a target letter, if it matched then a halting condition is achieved. Proximity to target with repect to the whole phrase is determined by the number of letters being searched for – when there are zero the target is found.

    Dawkins describes a process where the number of correct letters are summed to produce a score, a proximity, for the phrase as a whole, not for individual letters. The search is NOT partitioned up into individual letter searches, each with its own halting condition. The search mechanism does NOT halt for an individual letter when it matches, it halts when the sum of matching letters is equal to the number of letters in the phrase.

    These are important differences between the two, even if they sometimes produce similar behaviour. Glossing over this by trying to pretend that it is irrelevant to the content of the paper misses the point. It trivialises the whole subject of search algorithms. These are two different processes at work, it is inappropriate to describe them as being the same.

  231. I would say they are using the same algorithm just using it differently.

    It appears that they (D/M) are combining the outputs to get one.

    Ya see the intention is different- as I said above.

    Dawkins was trying to show how the ratcheting properties of cumulative selection will find a target much sooner than a random step-wise search.

    D/M were trying to show how that type of search does its job.

  232. Joseph,

    It appears that they (D/M) are combining the outputs to get one.

    If it means what I think it means (combine the correct letters of several parallel partitioned searches to get to the next phrase) then this is wrong. Just look at Eq22 again. Or at the text, which explains it will enough. And even IF it would be the way D+M were constructing the next parent string it would still be very different from Weasel. I thought you understood the difference earlier in this thread but it seems I was mistaken.

    How can one use the same algorithm differently anyway without using in fact a different algorithm? You could use different parameters (population sizes or mutation rates) for Weasel but you have no such choices for the partitioned search!

  233. PPS: I need correct Indium and DJ, that:

    1 –> The observed Weasel 1986 behaviour [o/p] requires a mechanism [i/p & processing] — i.e. the old I–> P –> O elements of a program — that explains its dynamics; of which explicit and implicit mechanisms are the two best candidates. [Is this a case where StephenB's "causeless events" problem for Darwinists is surfacing? I firmly believe -- on good grounds -- that unless necessary causal factors are present an event CANNOT happen, and unless sufficient ones are present it WILL not happen. So if it happens, we can identify causal factors and how they work -- i.e mechanisms. And given the issue of synergy -- effects due to interaction -- mechanisms do not have to be explicitly built and labelled as such. I do not believe in magical poofery!]

    2 –> In terms of Atom’s adjustable weasel, explicit latching corresponds to “partitioned search” and implicit latching will show up with cases under his “proximity reward search.”

    3 –> The decision that implicit mechanisms best explain the observed showcased runs of champions c 1986 is based in large part on Mr Dawkins’ subsequent testimony; understood as denying that Weasel explicitly latched.

    4 –> Once ratcheting behaviour exists, the eqn 22 from p. 1055 of the IEEE paper, suitably understood, applies. For instance — and here I took a correction on the interpretation of Q — with generational clustering, queries [= mutant pop members] come in generational bunches of size S: Q = G*S. And the latching-ratcheting o/p will apply to the run of generational champions; an observable behaviour.

    5 –> So, for instance with pop size = 50, queries to date will go 50, 100, 150 etc. corresponding to 1, 2, 3 etc times 50.

    6 –> Interesting, onlookers, how a concession that implicit latching is real can be made to look like a claim of victory for the Darwinists! (Hint: rhetoric is the art of persuasion, and too often works by making he weaker case seem stronger than it is. So, let us attend to the merits and facts, and follow back to the points where it was being ever so stoutly insisted that here was no evidence of latching in the Weasel o/p c 1986, or that latching only meant explicit latching, or that implicit latching did not happen or that implicit latching is a triviality etc etc.)

  234. Indium,

    D/M are explaining something that Dawkins’ wasn’t.

    So yes two different sets of people can use one thing to explain two different things.

    The confusion comes from yet another set of people who can’t understand that.

    And here you are…

  235. Interesting, onlookers, how a concession that implicit latching is real can be made to look like a claim of victory for the Darwinists!

    KF, the onlookers aren’t stupid, they can see that this whole “lets define latching to mean whatever we need it to mean in order to claim victory” is your own tactic, one you keep employing again and again.

    The onlookers who have been following this long enough will remember how you invented the ideas of implicit/quasi/semi-latching in order to get around the fact that al the published output of WEASEL can be explained without it requiring an EXPLICITLY DEFINED LATCHING MECHANISM – something Dembski and marks explicitly define for their algorithm but which Dawkins doesn’t.

    This concession over implicit latching is a fantasy of yours, in Dawkins algorithm the fittest member appears to latch some of the time without ever needing a latching MECHANISM. We all knew this from the start and pointed it out to you, you then invented the term “implicit latching” to describe this behaviour, and claimed that you were right about there being a latching mechanism all along.

    You are making a fool out of yourself, and of this website.

  236. The facts are that Dawkins used cumulative selection as a ratcheting process.

    He descirbes it as “slight improvements”.

    The way cumulative selection is described and illustrated in TBW it is a ratcheting process.

    And the only way around that is to contort what Dawkins actually wrote.

  237. I challenge anyone to find a passage or passages in TBW that would show that cumulative selection is not a ratcheting process. That reversals can happen and be selected.

    From the book only.

    Good luck…

  238. Joseph,

    I think you are confused. Dembski and Marks are using a different thing to explain a different thing but they cite Dawkins algorithm and make out it is the same, when as we have seen, it is actually different.

    They should have referenced a similar thing when explaining their thing rather than referencing a different thing than the one they explain.

    It is all very simple really!

  239. Onlookers:

    Re BillB: This concession over implicit latching is a fantasy of yours, in Dawkins algorithm the fittest member appears to latch some of the time without ever needing a latching MECHANISM . . .

    Sadly, this reveals that BillB is till well out beyond the pale of civil discourse:

    1 –> In the App 7, the always linked [dating to about April] we may see from point 12 on, after a presentation on what is to be explained, Weasel 1986:

    12 –> To explain the latching more realistically, we may have an explicit latching algorithm based on letterwise search . . . .

    13 –> Letterwise partitioned search is also a very natural way to understand the Weasel o/p in light of Mr Dawkins’ cited remarks about cumulative selection and rewarding the slightest increment to target of mutant nonsense phrases. As such, it has long been and remains a legitimate interpretation of Weasel. However, on recently and indirectly received reports from Mr Dawkins, we are led to understand that he did not in fact explicitly latch the o/p of Weasel, but used a phrasewise search.

    14 –> Q: Can that be consistent with an evidently latched o/p?

    ANS: yes, for IMPLICIT latching is possible as well.

    15 –> Namely, (i) the mutation rate per letter acts with (ii) the size of population per generation and (iii) the proximity to target filter to (iv) strongly select for champions that will preserve currently correct letters and/or add new ones, with sufficient probability that we will see a latched o/p. (This effect has in fact been demonstrated through runs of the EIL’s recreation of Weasel.)

    16 –> in a slightly weaker manifestation, the implicit mechanism will have more or less infrequent cases of letters that will revert to incorrect status; which has been termed implicit quasi-latching. This too has been demonstrated, and it occurs because an implicit latching mechanism is a probabilistic barrier not an absolute one. So, as the parameters are sufficiently detuned to make reversions occur, we will see quasi-latched cases. Sometimes, under the same set of parameters, we will see some runs that latch and some that quasi-latch.

    17 –> In a litle more detail, we will see reversions in a case where the odds of mutation per letter are sufficiently low that in a reasonable generation of size N, there will be a significant fraction of no-change members, and so the proximity filter will select no-change to be next champion, or a single step increment in proximity; or, in some cases a substitution where one correct letter reverts and one incorrect letter advances . . . .

    19 –> In short, there is almost no chance that such a mutant generation population will have no unchanged members. In that context, with the proximity filter at work, no-change cases or substitutions or single step advances will dominate the run of champions. Indeed, the Weasel 1986 o/p samples show that runs to target took 40+ and 60+ generations, i.e. no-change won about half the time and single step changes dominated the rest. No substitutions were observed in the samples, suggesting strongly that there were none in the showcased runs. (Double step advances etc or substitutions plus advances will be much less probable. But in principle, per sheer “luck,” we could see the very first random variant going right to the target. Just, the odds are astronomically against it. As, probabilistic barriers may be stiff, but are not absolute roadblocks.) . . . .

    24 –> In turn that means that a further key issue on champion selection per generation is the specific action of the proximity filter, in a context where — continuing the concrete example — the expected number of zero change cases in a generation is about 17, that for single step advances is about 1, and that for substitutions ranges from 1/2 down to 5/1000, depending on degree of proximity already achieved. That turns out to be a fairly complex issue:

    2 –> Given subsequent debates, I would adjust phrasing for clarity, but the point is plain: explicit mechanisms latch letters explicitly, and implicit ones do so out of the interaction of population size, mutation rate and filter characteristics. remember o/p is what we directly observe, and mechanism is based on the i/p’s and processing that give rise to it.

    3 –> That is, the issue of observed behaviour and its explanation by alternative mechanisms was long since addressed. It is not a latterday “concession,” but an alternative EXPLANATORY MECHANISM, one that — per inference to best, empirically anchored explanation — is in fact preferred on the balance of the evidence; ever since some time in March or so, when the information came to our attention at UD. (Remember, it is a DEMONSTRATED mechanism, as is for instance reproduced and/or linked above.)

    4 –> Therefore, it seems that BillB has regrettably failed to do his homework before criticising, and has indulged in pejorative mischaracterisation and misrepresentation.

    5 –> This pattern of uncivil rhetorical conduct is to be corrected on his part.

    GEM of TKI

  240. Joseph:

    [Weasel] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL

    Challenge met – no mention of a rule that prevents letters reverting. When you implement this you get a mechanism that works towards the target, revisions occasionally occur, as KF has demonstrated, and all published data is consistent with this.

    This is also consistent with the use of cumulative as paying attention to movement in one direction and not in the other, for example cumulative height or accumulated wealth.

  241. BillB – It has been pointed out to kf that latching is irrelevant to the original question, which is “Are D&M accurate when they call Weasel a partitioned search, and use eqn 22 to describe it?”
    We have been explaining this to kf in simple, plain english since post 34, where I said

    Forget about latching, you cannot have a partitioned search that changes only one element in its first iteration, and reaches a solution within 43…

    kf, OTOH, has resorted to re-defining the word “mechanism” (@232) in his increasingly desperate attempts to avoid admitting any mistake.
    Humpty Dumpty would be so proud.

  242. BillB,

    There isn’t anything in your quote that satisfies my challenge.

    No mention that letters, once matched, can be changed.

    That is what I am looking for and I made that clear.

    Also I have said that intellignet agencies can use “cumulative” in a different way.

    So if you are saying that evolution is guided by an intelligent agency then you would have a point.

    Otherwise “cumulative” along with the description of “slight improvements” only means ratcheting is taking place.

  243. I challenge anyone to find a passage or passages in TBW that would show that cumulative selection is not a ratcheting process. That reversals can happen and be selected.

    From the book only.

  244. DNA Jock,

    If we go by what Dawkins wrote in TBW then “weasel” is a partitioned search- ie ratcheting occurs.

    And we know ratchets can move in both directions but force is only applied in one.

  245. KF,

    Please could you at least try and understand what the debate is about.

    When Dawkins describes a mechanism that does not lock letters, and Dembski and Marks describe one that does, and both produce different behaviour, and Dawkins published behaviour is consistent with the algorithm he describes … and Dembskis is inconsistent with Dawkins output … and Dawkins specifies a population … and so on and so on …

    Why would any sane person still try and maintain that these are the same algorithm and that the citation is appropriate? Playing semantic games with words like latching doesn’t help your case at all, it just smacks of arrogant desperation and a total inability to acknowledge your own mistakes.

  246. I challenge anyone to find a passage or passages in TBW that would show that cumulative selection is a ratcheting process. That reversals can not happen and will not be selected.

  247. Joseph,
    ratcheting, latching, implicit, explicit, so many arguments are just based on semantics. What do you mean by ratcheting? A ratchet can only go in one direction, the algorithm Dawkins describes can go in both (just try it yourself with Atoms suite).

    In the TBW Dawkins says that the strings are copied with random errors/mutations. Since he does not limit this mutations to incorrect letters correct letters also mutate -> No ratcheting or latching at the mutation level. Agreed?

    This is of course in line with what Dawkins says, what is demonstrated in a video and with biological reality. And even with kairosfocus allways linked appendix 7. And with the EIL software.

  248. Indium,

    The way Dawkins describes cumulative selection as “slight improvements” can only mean it goes in one direcetion- towards the goal.

    Reversals as an improvement only work with agency involvement because agencies can plan ahead.

  249. BillB:

    I challenge anyone to find a passage or passages in TBW that would show that cumulative selection is a ratcheting process.

    That part has been presented already.

    It has to do with Dawkins talking about “slight improvements”.

    As soon as I get the book back I will provide the quotes.

  250. my two cents:

    Cumulative selection — increasing by successive additions — is indeed a ratcheting process so long as the string, chosen from the present generation, most closely representing the target phrase is closer to the target phrase than the parent string. The chances of reversal would depend on the size of the population and the mutation rates. Thus, within specific parameters, Dawkins algorithm will provide a ratcheting process (“implicit” latching since it is based on probability of reversion to a string further from the target) and within other parameters it will not provide a ratcheting process.

    So long as we see a steady closing in on the target, we are viewing a ratcheting process (whether it happens as a result of probability or explicit programming to achieve ratcheting behavior).

  251. It looks like my challenge cannot be met.

    No surprise there.

    I challenge anyone to find a passage or passages in TBW that would show that cumulative selection is not a ratcheting process. That reversals can happen and be selected.

    Without that all you anti-IDists are blowing smoke.

    Not only that you are accusing D/M of something that they didn’t do.

  252. No, Joseph, you are wrong.
    Dawkins’ narrative is clear to 99% of the people who have read it — “Random mutation” means random mutation as it is observed to occur in nature. In particular Dawkins refers to selecting the best “phrase” which makes little sense for a latching mechanism, and none for a partitioned search. “Cumulative” is used in contrast to the alternative “single-step”, or perhaps “instantaneous”. It is as telic as “In April, water accumulated in my wheel-barrow” which does not (to me anyway) deny the existence of evaporation.
    You are asking (I hope) a rhetorical question – “Where in TBW does it say There is no latching ?”. I might as well ask “Where is the KJV Bible does it say ‘Adam did not have three arms’ ?”.
    But, and this is the really important point, even if there were an explicit latching mechanism in Weasel, that would not make it a partitioned search as described by D&M. The first reported Weasel run in TBW CANNOT be the result of a partitioned search. Only two letters change in generation 2.

    Latching is irrelevant to the accuracy of D&M’s citation. I am accusing D&M of mis-citation when they claim that eqn22 describes Weasel. I encourage everyone to go to EIL and play with Atom’s adjustable Weasel, specifically the Proximity Reward Search, and contrast its behavior with that of the Partitioned Search.

  253. Joseph, it is not our fault that you seem to think that a cumulative process can´t also accumulate negative values.

    Weasel is a cumulative because the results from a search are the basis for the next search step.

    I have never seen such a desperate semantic argument before.

    So, maybe you can give me a straight answer to the following question, we can then proceed from there:
    In the TBW Dawkins says that the strings are copied with random errors/mutations. Since he does not limit these mutations in any way to incorrect letters this means correct letters also mutate -> No ratcheting or latching at the mutation level. Agreed?

  254. Indium,

    It is very telling that you cannot meet my challenge.

    It is also very telling tat all you have are desperate semantics.

    Again “cumulative” and reversals only make sense in an agency involved scenario.

    Non-telic processes would not see reversals as an improvement over the parent.

  255. DNA Jock,

    A partioned search is a latching/ ratcheting process.

  256. Joseph,

    I am in the process of explaining why you are wrong.
    So, can you give me a straight answer to my question:

    In the TBW Dawkins says that the strings are copied with random errors/mutations. Since he does not limit these mutations in any way to incorrect letters this means correct letters also mutate -> No ratcheting or latching at the mutation level. Agreed?

  257. Joseph,

    A partioned search is [insert] one type of [/insert] a latching/ ratcheting process.

    Fixed that for you.

    Perhaps you meant to say
    “A latching process is (necessarily) a partitioned search (as modeled in eqn22)”
    But that would be wrong.

    Or you meant to say “Weasel is a partitioned search (as modeled in eqn22)”
    But that would be obviously wrong.

  258. I like Joseph’s demand for proof from the text of TBW that it explicitly precludes ratcheting. Somewhat akin to asking for proof that God (sorry, an intelligent designer) doesn’t exist. And in both cases the response is the same: instead of demanding proof for the non-existence of something, why not provide proof for its existence? In the case of WEASEL, please do what BillB asked for in #245.

    I suspect that TBW doesn’t explicitly say “positions aren’t latched once they have their correct values” because such an outrageous hack would never have occurred to RD. It just doesn’t represent what he was trying to model.

    Joseph, please just confirm that you understand this: letters don’t revert to incorrect values because the candidates that do are never the fittest amongst the generated offspring. This is true even for small values of n (about 50 from my experiments, depending on p(mutation)). Make n smaller, and yes, you WILL see reversions, and in the limit, as n -> 1, you’re basically making a random mutation to a single offspring, and off course you’ll never get closer to matching the environment string (unless you employ ratcheting, a la D/M). You do understand all this, right?

    On this issue of “the program contains information that allows it to solve the problem” as raised by kf and others, I disagree: this is just an implementation detail. Instead of the target string being harcoded into the program (or input at the start), let’s read it from an input stream instead. Moreover, let’s read it at the start of every generation, allowing it to change over time. The program will still work just as well, even though its only knowledge of the target string is garnered at the beginning of each generation, making it similar to an “environment” in which the offspring are generated that I mentioned in a previous post; the progeny that goes forward to the next generation is the one that fits best the current environment, not some predetermined “distant target”.

  259. At least I can put the onus that no one answers to my edits on the fact that these stay in moderation for a half a day and not on a lack of quality of the edits themselves :-)

  260. Joseph and CJY:

    Thanks. Appreciated.

    It seems the Darwinists — oh, the irony! — are in denial.

    Maybe, they need to read this classical philosophical story, and then “wheel and tun and come again.”

    I think a spiritual issue is at the root. I suggest meditation and prayer on the lines of this classical text from the Sermon on the Mount.

    G’day.

    GEM of TKI

    PS: Onlookers, it seems BillB thinks I am now “insane” and/or “stupid” — sounds familiar? — to have (months ago) analysed, identified and defended then DEMONSTRATED the mechanism that triggers implicit latching as an explanation of Weasel 1986 [probably the only reason why it is suddenly "obvious" to all and why it is held that it is my intellectual incapacity that prevents me from seeing it in his estimation!], and to point out that the Marks and Dembski analysis starts from credibly OBSERVED ratcheting (oops, he apparently denies that the cumulatively selected o/p of Weasel 1986 evidently latches!), and deduce its implications for active information. This, from one who evidently has a difficulty with explanation of program o/p’s by credible causal mechanism tracing to i/p’s and processing behaviour. There is something plainly deeply and sadly wrong in the state of Darwinland — and it isn’t the name of the river of Egypt.

    PPS: Nephmon similarly, cannot agree that targetted search — with a built-in target phrase! — using a proximity to target filter to “cumulatively select” increments of proximity of “nonsense phrases” is a case where “the program contains information that allows it to solve the problem.” [He needs to read what CRD said in his own words on this, as is repeatedly cited above, e.g. last at 221, and as is explained in my online note app 7].Something is indeed deeply, sadly wrong in the state of Darwinland.

  261. kf:

    PPS: Nephmon similarly, cannot agree that targetted search — with a built-in target phrase! — using a proximity to target filter to “cumulatively select” increments of proximity of “nonsense phrases” is a case where “the program contains information that allows it to solve the problem.”

    What’s the conceptual difference between “proximity to target” and “fitness to environment”? In both cases some offspring fail to reproduce (all but one in the harsh world of WEASEL). In the natural world, it’s the lack of reproductive success caused by poor fitness to the environment. In WEASEL this is simulated in a very simplistic way by representing the environment as a “perfect gene” that would be the fittest possible for the world it inhabits, and relative fitness is represented as “closeness” to that gene. What’s the fundamental flaw with this?

    Actually, I did mention what RD had to say about the drawback of the program containing the target phrase, and I said that I think it’s an implementation detail. How “external” to the running code of the program would you need the target/environment to be before you accepted that the program itself didn’t contain the “information” that it’s working on? I already posited an example where the string could be read from an input stream, the other end of which could be a program running halfway across the world. Is that external enough?

    If one states the problem as “show how the successive choice of the fittest of a group of randomly mutated offspring to be the sole parent of the next generation can quickly converge on the optimally ‘fit’ entity,” you need at some point to provide a quantity to measure fitness against. For convenience, it can be hardcoded into the program itself, but as I’ve mentioned a few times now, that isn’t necessary for the program to function, neither is it necessary for the target to be static.

    Out of interest, in what way does WEASEL fail most egregiously as a simulation of natural selection as you think it’s accepted by evolutionists? As I’ve freely admitted before, there are many simplifications implicit in it, but of the major components of “the natural selection of fittest offspring that are subject to random mutation”, where to you feel WEASEL most comes up short? (Please don’t concentrate on the “natural” aspect; by definition any simulation won’t be “natural” – there isn’t really mutating DNA in the computer.)

  262. Also, can you explain how what you term as “implicit latching”, i.e. lack of reversion of correct letters to incorrect ones, which is a result of the strategy of selecting the fittest of a large population of offspring, is fundamentally different from what’s observed at in real organisms at the gene level?

    If the human genome mutates at, say, 100 bases pairs per sexual reproduction (which is towards the upper bound of the estimated range), what’s the chance of any of those 100 out of the 3.4 billion or so base pairs in the genome are going to mutate back again in the near (or even distant) future? Rather small, I’d imagine. Thus once a beneficial mutation has made it into the genome, it will very likely be passed down for all intents and purposes “forever”, in other words, it’s latched. In what way is this different from happens in WEASEL?

  263. I try it again:
    In their paper, Dembski and Mark they start with the phrase:
    SCITAMROFN*IYRANOITULOVE*SAM
    I calculated a next generation using Dawkins’s algorithms with populations of 10,50 and 100 – and mutation rates of .04, .05 and .1. The tenth string in the list is the second generation given in the paper of Mark and Dembski. The differences with the first generation are in bold face:

    1. SCITAMROFN*IYRANOIEULOVE*SAM
    2. SCITAMROFN*IYRANOITULOGE*SAM
    3. ECITAMRI*N*IYZANOITULOVE*SAM
    4. SCITAMROFN*IYRANOITUL*VE*SAM
    5. SCITAMROFN*IYRANOITULOVE*SEM
    6. SCITAMOOLNOIYRAMOITULOVE*SEM
    7. SCITANROFN*IYYANOITULOVE*SAM
    8. SCITIMROFN*JYRANOITULOVE*SAM
    9. SCITAMROFN*ICRHNOITSLOWE*SAV
    10. OOT*DENGISEDESEHT*ERA*NETSIL
    kf – can anyone spot a difference in the design of the strings? Could you explain why it exists?
    Heck, I even calculated the probabilities for latching
    (I hope I don’t have to endure another twelve hours of moderation…)

  264. Nephmon:

    You have asked an excellent question here, that goes to the heart of the issues at stake:

    What’s the conceptual difference between “proximity to target” and “fitness to environment”? In both cases some offspring fail to reproduce (all but one in the harsh world of WEASEL). In the natural world, it’s the lack of reproductive success caused by poor fitness to the environment. In WEASEL this is simulated in a very simplistic way by representing the environment as a “perfect gene” that would be the fittest possible for the world it inhabits, and relative fitness is represented as “closeness” to that gene. What’s the fundamental flaw with this?

    1 –> I first ask you to simply read the weak argument correctives above [and while you are at it you might want to take a look in a library at the Schutzenberger contributions on functional complexity dating all the way back to the Wistar high level summit of 1966], then take as look at the always linked, starting with the App 7, especially where it discussed the back-story on Weasel:

    10 –> Back story: Mr [Fred] Hoyle had raised the issue that the origin of a first life form — such as, roughly, a bacterium — is a matter of such complexity that the odds of that happening in a prebiotic soup by chance was negligible. In a more up to date form, this is the challenge that is still raised by the design theory movement: life shows a threshold of function at about 600,000 bits of DNA storage capacity, so before one may properly apply hill climbing algorithms to scale Mt Improbable, one needs first to have a credible BLIND watchmaker mechanism to land one on the shores of Isle Improbable; e.g. drifting by reasonable random configurations of molecules in empirically justified pre biotic soups and empirically credible pre-life selection forces. (But . . . this OOL challenge is still unmet. And similarly . . . the origin of body plan level biodiversity requiring 10′s – 100′s or millions of bits of functional genetic information, dozens of times over, is equally unmet.)

    11 –> So, it looks uncommonly like Weasel distracts attention from and begs the question. That sums up the balance on the main issue . . .

    2 –> In short, there is a major question-begging — indeed, dismissal: “single-step selection” — at stake in Weasel as presented: the origin of complex, functionally specific information.

    3 –> that is, until one has spontaneously created novel complex information that functions through similarly sophisticated but spontaneously originated machinery, at a realistic level, one has no right to pretend that a targetted process that uses a hotter-colder distance-to target comparison of “mutant nonsense phrases” — i.e confessedly NON-FUNCTIONAL ones — is a good analogy of the power of random variation and natural selection, which is premised on the origin of information by chance variation, and the selection of FUNCTION on superiority of some sub-populations.

    4 –> that was the heart of Sir Fred’s challenge and it is the heart of the design theory challenge to the claimed spontaneous origins of life and of novel body plans. That is, we do observe FSCI of an order of complexity of 1,000 or morte bits forming all the time: by DESIGN. But, we have never observed this by spontaneous forces tracing to chance + necessity without intelligent intervention. And, on search resource exhaustion grounds — as CRD actually concedes in the relevant passage — it is utterly implausible that we will ever get to such complex functionality on the gamut of our observed cosmos. [And please resist the red herrings and strawmen in the usual rebuttals of Hoyle a la Wikipedia. Remember you are in the presence of a Nobel Prize equivalent holder here. he may be wrong on points, but he is not going to be making simplistic blunders, and even his errors will be instructive. That is my experience from many years of running across his work, on a wide array of topics, starting with the Steady State universe Hypothesis. (He it is who gave the name "big bang" to the cosmogenetic theory of that name, but he did not intend it to be a positive term.)]

    5 –> With these points in mind, let us look again at what CRD said in discussing Weasel:

    _________________

    >> It . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate [i.e. search resources come in here --KF], would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed . . . .

    Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection, although human vanity cherishes the absurd notion that our species is the final goal of evolution. In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success. [TBW, Ch 3, as cited by Wikipedia] >>
    _________________

    6 –> In short, CRD acknowledges that the so-called fitness function he uses is nothing but a measure of distance to target which ignores and even dismisses the issue of first needing to be on at least the shoreline of an island of complex function before hill-climbing through warmer-colder signals can be reasonable.

    7 –> Thus, he inadvertently testifies that it is the injection of artificially originated active information that makes the difference in achieving complex function within reasonable search resources.

    8 –> We should note that he also realises at some level that the substitution he makes is “misleading.”

    9 –> Indeed.

    10 –> Finally we should note that genes are in effect informaiton storage devices. Until the functional machines to interpret and carry out the information exist, they are jut polymer molecules. And, the machines in question have to be coded for and organised to function: ~ 600 – 1,000 k bits of info based on observed life. (Just 1,000 bits specifies a config space so large that the 10^80 or so atoms of our observed universe across its credible lifespan will not be able to scan through 1 in 10^150 of that, effectively the scope of feasible search is a fraction not materially different from zero.) This is the basic reason why OOL is such a challenge to evolutionary materialism.

    11 –> And, when it comes to origin of body plans de novo, we are talking of not 600 – 1,000 or so k bits of information but 10′s – 100′s of mmega bits, all of which have to be in place before function is feasible.

    GEM of TKI

  265. As I said before:

    …even if there were an explicit latching mechanism in Weasel[and all the evidence indicates that there is not one], that would not make it a partitioned search as described by D&M. The first reported Weasel run in TBW CANNOT be the result of a partitioned search. Only two letters change in generation 2.

    Latching is irrelevant to the accuracy of D&M’s citation. I am accusing D&M of mis-citation when they claim that eqn22 describes Weasel. I encourage everyone to go to EIL and play with Atom’s adjustable Weasel, specifically the Proximity Reward Search, and contrast its behavior with that of the Partitioned Search.

    Now don’t I deserve some of your delicious word salad, kairosfocus?
    Please may I have some more?

  266. Except that latching/ ratcheting makes it a partitioned search.

    That is if you understand English…

  267. Joseph#265

    Except that latching/ ratcheting makes it a partitioned search.

    Explicit latching makes it a form of partitioned search. Dawkins algorithm does not explicitly latch.

  268. I would like to publicly thank Mrs. O’Leary for getting me removed from the banned list. She has been very gracious in private email, albeit strangely fascinated with hockey. ;-)

  269. Joseph, I understand that you are going for the second door:
    “A latching process is (necessarily) a partitioned search (as modeled in eqn22)”
    which is a much better choice than the third door:
    “Weasel is a partitioned search (as modeled in eqn22)”, which is blatantly wrong.

    The key aspect of the partitioned search is that it is a “divide and conquer” procedure(p1055), in which the search for each character is independent of the search for the other characters. Thus for partitioned search without sample replacement, the target can be found in N-1 queries (p1056) irrespective of the target length. There are whole categories of search algorithms that work by step-wise comparing a short search string (one or two letters) with the target (starting at one end and moving along until a match is found.) This information is then used to infer the FOO (p1054) for the target, and subsequent short search strings use the derived FOO. Useful if the FOO is unknown.
    It latches, but it ain’t a partitioned search.

  270. KF:

    The issue of WEASEL’s biological relevance is separate and unrelated to the issue of whether the citation in Dembski and Marks paper is accurate.

    You have demonstrated that WEASEL does not require an explicit latching mechanism to produce any of the observed results, as we have been saying all along. Given this fact, and Dawkins description, and his statements about latching mechanisms, your claim that the existence of an explicit latching mechanism is a reasonable interpretation is not valid.

    Joseph:

    Latching individual letters is a partitioned search, ratcheting towards a target is only a partitioned search if individual letters are locked out of the search when they reach their target.

    Partitioning means to divide up the search into separate, independent units. WEASEL is not an algorithm that searches for individual letters, it is not partitioned.

  271. Kairosfocus-
    You gave Nephmon 1,259 words of tasty word salad, changing the subject to abiogenesis and arguing from the authority of dear departed Fred Hoyle.

    4 –> that was the heart of Sir Fred’s challenge and it is the heart of the design theory challenge to the claimed spontaneous origins of life and of novel body plans. That is, we do observe FSCI of an order of complexity of 1,000 or morte bits forming all the time: by DESIGN. But, we have never observed this by spontaneous forces tracing to chance + necessity without intelligent intervention. And, on search resource exhaustion grounds — as CRD actually concedes in the relevant passage — it is utterly implausible that we will ever get to such complex functionality on the gamut of our observed cosmos. [And please resist the red herrings and strawmen in the usual rebuttals of Hoyle a la Wikipedia. Remember you are in the presence of a Nobel Prize equivalent holder here. he may be wrong on points, but he is not going to be making simplistic blunders, and even his errors will be instructive.
    [Emphasis added]

    Soooo, “tornado in a junkyard makes a 747” is an appropriate analogy because an eminent guy once said so and we should “resist the red herrings and strawmen” that might disagree.
    Now, I might be persuaded that Sir Fred was a “Nobel Prize equivalent holder”, but I am certainly not in his presence, any more than I am in Sir Isaac’s presence (A man with some very interesting ideas about the Philosopher’s Stone and about the Holy Trinity, by the way). Much has been learnt since these eminent gents passed on, and if they were alive today, they might disagree with their previously held beliefs.

    And, anyway, it is an argument from authority. Again (see post 136).

    One small request though : could my word salad be on topic – whether eqn22 could possibly describe TBW Weasel? Thanks.

  272. What a fascinating discussion! Most interesting, for me, is the parallels with the philosophies of the participants.

    KF and Joseph, being creatures of Faith, clearly need there to be latching, even if it doesn’t exist, because certain prophets say it exists in the original Weasel. Now, they can’t say that the prophets are wrong, despite the objective evidence, otherwise the rest of the philosophy as espoused by the prophets is questionable. So they go through all kinds of linguistic contortions to claim latching exists, even to the point of defining “latching” as something it isn’t.

    As in this thread, so in their religious philosophies. For “latching” read “God”.

  273. LOK Gaz@272. So in other words, “Latchingdidit” :D

  274. Did I really manage to mistype “LOL”? Shurely shome mishtake!

  275. kf: I’m very impressed by your ability to cite background material, use long words, and deflect the topic in order to suit your purposes. You ability to answer simple questions clearly and succinctly, not so much.

    I asked about the differences between the mechanism of natural selection and its first-order approximation in WEASEL. You answered by talking about Hoyle’s views on the origin of life.

    (Aside: Creationists love to harp on about Darwin’s “racism” as though [if it were true] it invalidates everything else he has to say. But they don’t mention much about the astonishing sexism in some of Hoyle’s novels. Oh wait,I guess Hoyle was just a product of his time.)

    Anyway, by definition, WEASEL is “picking up the story” some way down the line from its beginning. You can hark back to the start of it all if you like, but it’s not really salient to this discussion.

    In any simulation and discussion of it, there have to be some “givens”. Unfortunately, you don’t seem to be prepared to “give” anything, so it makes it hard to have a reasoned debate with you.

    I totally disagree with your point (3) in 264. The distance of a given letter sequence from the target in WEASEL is a model of a gene’s fitness to its environment. There fore it is “a good analogy of the power of random variation and natural selection, which is premised on the origin of information by chance variation, and the selection of FUNCTION on superiority of some sub-populations,” because that distance is the way we happen to modeling functionality. You could easily imagine a much more sophisticated model where the letter-sequence is transformed into an object (in the computer science sense) whose attributes allow it to perform better or worse in a virtual world.

    Simple example to make it more concrete: the first letter of sequence corresponds to length of the neck of the virtual creature. One of the attributes of the environment is the average and SD of the height of foliage on the virtual world’s trees. Part of the candidate sequence’s “fitness” is how well its phenotype’s neck length enables it to feed. This is just a more involved simulation than “the Hamming distance between the first letter of the sequence and the “m” of “methinks”, but doesn’t alter the fundamental nature of it.

  276. nephmon:
    I’m afraid KF will probably regale you with his conspiracy theory about Lewontin and how evolution is all a materialist plot that depends on a material origin of life, which means OOL is relevant to everything, apparently.

    I suspect that if a step by step origin of life is ever established, KF will most likely say that it begs the question of where matter came from, and that that was the issue all along, and by concentrating on OOL we were simply distracting with clouds of oil of ad hominem burning straw men meant to poison and confuse …

    I’m tempted to see what would happen if you gave one group of computer science students Dawkins WEASEL description, gave another group Dembski and marks’ description, and asked them both to implement the algorithm as described without any other prompting or background.

    I can’t imagine either group ever producing anything close to functionally equivalent programs. There is just no way you can read those two descriptions, implement them, and come up with the same piece of software.

  277. nephmon (274),

    “Did I really manage to mistype “LOL”?”

    Don’t worry, the God of Latching will get that K to an L in no time – and keep it there!

    “Shurely shome mishtake!”

    Are you another “Private Eye” reader?

  278. Agreed, Bill. Actually, I’ve been thinking it would be an interesting interview question for a software developer candidate (implementing WEASEL, not necessarily doing a comparison with D/M). If they start talking about specified complexity, I’ll know to lower my expectations :D

  279. Mrs O’Leary (and onlookers):

    I have been wondering why the Darwinists have been so caught up in trying to prove Messrs Demsbski and Marks wrong on Weasel, especially in the context where it is pretty clear from the remarks made by Mr Dawkins, that:

    1] Weasel’s performance gain over unassisted random walk search is due to the presence of an embedded target, with a warmer-colder proximity based filter that rewards mere proximity of “nonsense” – non-functional — phrases.

    2] Thus, Weasel works by and demonstrates the power of active information, as is being introduced by the cluster of current Marks and Dembski articles from the EIL.

    3] Weasel also shows cumulative selection, which was showcased by a the “famous” 1986 runs that showcased how the progress to target in the sampled runs is without reversion. (This is consistent with the basic, plain garden untwisted meaning of “cumulative”: Increasing or enlarging by successive addition. A sense that we have every reason to see from his descriptions and examples as the one intended by Mr Dawkins c 1986 in BW; latterday “revisionising” notwithstanding.)

    4] two mechanisms have been shown — yes, SHOWN — capable of producing runs of generational champions that produce the same effect: (i) ratcheting action based on explicit latching of successful letters to date in Weasel, and (ii) ratcheting action produced by implicit latching due to interaction between selected population sizer per generation, mutation rate per letter and selection filter characteristics.

    5] Mr Dawkins has more or less has said that the actual code for Weasel c 1986 is not forthcoming, but the various algorithms and programs currently on the web are good enough to replicate the essential action, whch seems to have been implicit not explicit.

    6] Once we see such generation champion ratcheting action, as marks and Dembski analyse in their IEEE paper, p. 1055, an analysis of its implications compared to the performance of a baseline random walk gives us a reasonable measure of the impact of the active information involved in the targetting and warmer-colder proximity mechanisms.

    So, why is there so much digital ink being spilled in an attempt to discredit the above?

    ANS: I think we first need to recognise that over the past decade or so, the standard rhetorical tactic regarding the work of Dr Dembski has been to try to tag him as an ignoramus and bumbler, who does not know what he is talking about and is misleading ill-informed followers. To that end, it has been a routine to twist his terms and analyses, making up ad homiem laced strawmen that have been ignited to cloud, confuse and polarise the atmosphere.

    Such ruthless, manipulative and misleading rhetoric has been becoming increasingly threadbare in recent years, and the ongoing collaboration with a distinguished Electrical Engineering professor makes the holes in the elbows, the frayed cuffs and the frayed collar quite plain. So, the above plainly reflects an attempt to renew the old rhetorical line and give it new talking points.

    It is in that context that we need to pick up some “highlights” overnight:

    1] DNA-J, 265: …even if there were an explicit latching mechanism in Weasel[and all the evidence indicates that there is not one], that would not make it a partitioned search as described by D&M. The first reported Weasel run in TBW CANNOT be the result of a partitioned search. Only two letters change in generation 2.

    The essential point in partitioning, according to M & D [p. 1055], of course – from their example — is that “Two of the letters {E, S} are in the correct position . . . In partitioned search, our search for these letters is finished . . . “ (That is, a partitioned search is one that identifies correct letters individually and by one mechanism or another preserves them from reversion, so that he progress of the run of generational champions is ratcheted, with the successful letters being latched. Latching of coruse means: “To close or lock with or as if with a latch.”)

    In short, we see here a plain strawman distortion, led off by the direct denial of the evidence from the actual showcased runs of “cumulative selection” in action. For, in the actual case from 1986, in 200+ cases of letters that could revert, none do, AND where we see incorrect letters, they typically persist across at least one decadal sample.

    This sort of sleazy rhetoric is simply not good enough.

    2] DL, 267: Explicit latching makes it a form of partitioned search. Dawkins algorithm does not explicitly latch.

    This red herring led out to a strawman conveniently omits the other possibility: IMPLICIT latching, which is a main point of the discussion above.

    And, since we have learned of Mr Dawkins’ claims since about 2000, it is implicit latching that has been the inferred best explanation of the behaviour of the showcased runs of Weasel c. 1986. For instance, I again excerpt App 7 my always linked, dating to April:

    13 –> Letterwise partitioned search is also a very natural way to understand the Weasel o/p in light of Mr Dawkins’ cited remarks about cumulative selection and rewarding the slightest increment to target of mutant nonsense phrases. As such, it has long been and remains a legitimate interpretation of Weasel. However, on recently and indirectly received reports from Mr Dawkins, we are led to understand that he did not in fact explicitly latch the o/p of Weasel, but used a phrasewise search.

    14 –> Q: Can that be consistent with an evidently latched o/p?

    ANS: yes, for IMPLICIT latching is possible as well.  

    15 –> Namely, (i) the mutation rate per letter acts with (ii) the size of population per generation and (iii) the proximity to target filter to (iv) strongly select for champions that will preserve currently correct letters and/or add new ones, with sufficient probability that we will see a latched o/p. (This effect has in fact been demonstrated through runs of the EIL’s recreation of Weasel.)

    At minimum, this is culpable, irresponsible negligence of duties of care to truth and fairness; at worst, it reflects blind parroting of outright willful deception by misdirection. (DL: It is all too easy to swallow the Darwinist partyline talking points and fail to check whether they are true and reflect the whole truth. So, a $64,000 Question: if the Darwinist leaders (remember men like Dawkins and Elsberry are involved in this since Dec last) are so unreliable and incompetent or on evidence that is directly accessible – indeed in front of them – why should we feel inclined to trust their reconstructions of a remote, unobserved world in the remote past?)

    3] DNA-J, 269: for partitioned search without sample replacement, the target can be found in N-1 queries (p1056) irrespective of the target length.

    The basic problem? Here is the M & D analysis of partitioned search in the IMMEDIATE context of Weasel, p. 1055:

    Assuming uniformity, the probability of successfully identi-fying a specified letter with sample replacement at least once in Q queries is 1 – (1 – 1/N)Q, and the probability of identifying all L characters in Q queries is

    q = (1 – (1 ? (1/N))^Q)^L . (22)

    Red herring led out to strawman again.

    4] BillB, 270: The issue of WEASEL’s biological relevance is separate and unrelated to the issue of whether the citation in Dembski and Marks paper is accurate. You have demonstrated that WEASEL does not require an explicit latching mechanism to produce any of the observed results, as we have been saying all along. Given this fact, and Dawkins description, and his statements about latching mechanisms, your claim that the existence of an explicit latching mechanism is a reasonable interpretation is not valid.

    First, the whole point of Weasel in BW was to create the impression via computer simulation, that complex biological information can be created de novo out of cumulative small random walks and cumulative natural selection. It is therefore highly relevant to observe that the simulation in question used targetted search with the target information preloaded, artificial selection of NON-FUNCITONAL “nonsense phrases” on mere proximity, and so begged the question in ways that Dawkins was forced to admit were “misleading.” (He doubtless relied on the rhetorical difference in impact between a spectacular simulation and the weasel words that qualified it.)

    Secondly, the reality of implicit latching has been hotly contested by Darwinists, and that has been so right up until I again reproduced actual implicitly latched runs of generational champions. So, the pretence that Darwinists have been saying that Weasel does not require an explicit latching mechanism to produce ratcheted progress to target — notice, onlookers, the clever omission of just what those “observed results” were – is a brassy distortion of the truth. Worse, as can be seen from 2 above, from March-April on, the implicit mechanism was advanced and documented: this is the false presentation of my longstanding argument as thought it were a latterday concession.

    And, there is a further ad hominem-laced strawman: I have pointed out that on the evidence of Weasel runs and commentary on cumulative selection c. 1986, explicit latching is a letgitimate interpretation. I have also made the specific distinction that on the CLAIMS of Mr Dawkins we have been willing to accept that Weasel 1986 did not explicitly latch. (And, as already repeatedly noted, videotaped runs c. 1987 are not decisive evidence of the state of Weasel c. 1986.)

    Of course, absent CREDIBLE WEASEL CODE c. 1986 — and this is the reason for the contest question 10 – we have no definitive answer beyond all doubt as to the state of Weasel c. 1986 as manifested in the runs published at that time.

    But, a subtler point lurks, as can be seen from the point 2 above: the Darwinist rhetorical intent is plainly to pretend that the D & M argument only applies to explicitly latched Weasels, so is a “misrepresentation” of Dawkins’ only implicitly latched Weasel. (This has in fact been claimed by Darwinists, above.)

    [ . . . ]

  280. 5] On ratcheted search and implicit latching.

    Now, the observations to be accounted for are the Weasel runs c 1986 as excerpted and showcased. In these runs, it is strongly evident that with high probability on “good runs” Weasel latched already correct letters for its generational champions and so ratcheted to target. Such behaviour can be achieved explicitly or implicitly, as has been demonstrated.

    Now, too, when we interpret queries as being in effect mutant phrases, we see that the output to be accounted for is not raw queries, but generational champions.

    So, we see that Q = G*S, i.e. queries to date are the number of generations so far times size per generation, and we observe too that his generational clustering can be done for BOTH explicitly latched and implicitly latched versions of Weasel. That is, in an explicitly latched Weasel, we can set up a cluster of mutants on the generational seed, and then use the proximity filter to pick the closest to target, reporting it as generational champion. In the case where we have implicit latching, we similarly pick the champion on proximity to target.

    The difference between the two cases is that in the explicit case the successful letters to date are masked off by direct instructions in the code. By contrast, in an unmasked case, once population per generation, mutation rate per letter and filter are such that there will be a high probability of no-change cases in the generations, and the dominant changed case is the single letter change, the dynamics – BTW another word for “mechanism” [AmH D: 3. An instrument or a process, physical or mental, by which something is done or comes into being ] — at work will tend to either preserve distance to target so far, or give a single step advance. (If the population size is large enough for a given mutation rate, double mutations may turn up in enough numbers that a reversion and substitution advance may happen: a correct letter reverts, and a previously incorrect one advances, preserving closest so far distance to target. This, too, has been demonstrated and may be important especially in “closing the deal” towards the end of the run. Such a run will tend to show what has been called quasi-latching: ratcheting with occasional slips as commonly happens when the dog on a baitcaster reel is wearing down.)

    Indeed, the showcased 1986 runs hit target in 40+ and 60+ generations, so no-change wins the generational contest about half the time, and single steps dominated the rest. (Recreations have bracketed this range, some being faster, some slower.)

    Then we see that the same mathematics of ratcheting applies to both. Just, we must observe that Q jumps in lumps of size G*S, and that ratcheting in the relevant sense attaches not to individual members of the population but the run of generational proximity to target champions.

    That mathematics of course gives mathematical substance to Mr Dawkins’ observation c. 1986 that targetted, proximity-rewarding search massively speeds up run to target relative to unassisted random search. This can be seen in the EIL adjustable Weasel, where unassisted search does ot converge in any reasonable time, but both the explicitly latched and the proximity reward case do. For the latter, once population size, mutation rate and filter are working together “right” implicit latching happens often enough to be reasonably observable.

    6] BillB, 270: Latching individual letters is a partitioned search, ratcheting towards a target is only a partitioned search if individual letters are locked out of the search when they reach their target.

    Agenda-serving question-begging definition imposed after the fact to be contentious.

    7] DNA-J, 271: changing the subject to abiogenesis and arguing from the authority of dear departed Fred Hoyle . . . . Soooo, “tornado in a junkyard makes a 747” is an appropriate analogy because an eminent guy once said so and we should “resist the red herrings and strawmen” that might disagree.

    Of course a glance at 264 in response to 261 gives a very different picture from the above strawman distortion:

    take as look at the always linked, starting with the App 7, especially where it discussed the back-story on Weasel:

    10 –> Back story: Mr [Fred] Hoyle had raised the issue that the origin of a first life form — such as, roughly, a bacterium — is a matter of such complexity that the odds of that happening in a prebiotic soup by chance was negligible. In a more up to date form, this is the challenge that is still raised by the design theory movement: life shows a threshold of function at about 600,000 bits of DNA storage capacity, so before one may properly apply hill climbing algorithms to scale Mt Improbable, one needs first to have a credible BLIND watchmaker mechanism to land one on the shores of Isle Improbable; e.g. drifting by reasonable random configurations of molecules in empirically justified pre biotic soups and empirically credible pre-life selection forces. (But . . . this OOL challenge is still unmet. And similarly . . . the origin of body plan level biodiversity requiring 10’s – 100’s or millions of bits of functional genetic information, dozens of times over, is equally unmet.)

    11 –> So, it looks uncommonly like Weasel distracts attention from and begs the question. That sums up the balance on the main issue . . .

    2 –> In short, there is a major question-begging — indeed, dismissal: “single-step selection” — at stake in Weasel as presented [c. 1986]: the origin of complex, functionally specific information.

    3 –> that is, until one has spontaneously created novel complex information that functions through similarly sophisticated but spontaneously originated machinery, at a realistic level, one has no right to pretend that a targetted process that uses a hotter-colder distance-to target comparison of “mutant nonsense phrases” — i.e confessedly NON-FUNCTIONAL ones — is a good analogy of the power of random variation and natural selection, which is premised on the origin of information by chance variation, and the selection of FUNCTION on superiority of some sub-populations.

    4 –> that was the heart of Sir Fred’s challenge and it is the heart of the design theory challenge to the claimed spontaneous origins of life and of novel body plans . . .

    Nor am I citing Hoyle as an authority to be bowed down and worshipped – not least, onlookers, one may look at App 1 the always linked where I have addressed the thermodynamics and information origination issues at what I believe is a useful introductory level, and in my own voice. (Notice how the Darwinists habitually dismiss or pointedly ignore easily accessible material evidence that does not suit their rhetorical agenda.)

    Worse, this is what I actually said about Mr Hoyle (and note the part that was conveniently omitted from the cite without even a ellipsis to warn the reader):

    Remember you are in the presence of a Nobel Prize equivalent holder here. he may be wrong on points, but he is not going to be making simplistic blunders, and even his errors will be instructive. That is my experience from many years of running across his work, on a wide array of topics, starting with the Steady State universe Hypothesis. (He it is who gave the name “big bang” to the cosmogenetic theory of that name, but he did not intend it to be a positive term.)

    In short, just the opposite to blind adherence to authority, I am saying that you need to treat competent workers with respect and highlighted how a major error of Sir Fred Hoyle – the Steady State theory – was highly instructive!

    Worse, this was suppressed and distorted by use of half-truthful selective citation in 271, which HAD to be deliberate. This is utterly inexcusable.

    [ . . . ]

  281. 8] Gaz, 272: KF and Joseph, being creatures of Faith, clearly need there to be latching, even if it doesn’t exist, because certain prophets say it exists in the original Weasel.

    This commenter should do his homework first: it is Joseph and I who have been showing the credible presence of latching action in Weasel c 1986 as can be deduced from the o/ps and discussion at that time. We have never appealed to any authority beyond Dawkins to show that – and that only to show what was showcased and what was said about it.

    Gaz needs to first show that there is a better explanation of the evidence c 1986, other than the “don’t believe yer lyin’ eyez” type of argument.

    As to the sneer on “faith” the only faith we have used here is the faith that an inference to best explanation is a legitimate piece of empirical investigation.

    9] NM, 275: I asked about the differences between the mechanism of natural selection and its first-order approximation in WEASEL. You answered by talking about Hoyle’s views on the origin of life.

    Misrepresentation based on selective summary.

    The key question I answered was yrs in 261, as I bolded in 264: What’s the conceptual difference between “proximity to target” and “fitness to environment”?
    Such a question NATURALLY raises the issue of the biological and pre-biotic realities and challenges of information generation, and I referred all the way back to Wistar 1966, where Schutzenberger et al challenged the Darwinist elites on the issue of plausibly getting to complex information-rich functionality by the mechanisms they champion. Hoyle picked up the same theme,a nd it continues unanswered to this day, misdirections such as Weasel notwithstanding.

    I then specifically addressed the difference between proximity and complex function:

    3 –> . . . until one has spontaneously created novel complex information that functions through similarly sophisticated but spontaneously originated machinery, at a realistic level, one has no right to pretend that a targetted process that uses a hotter-colder distance-to target comparison of “mutant nonsense phrases” — i.e confessedly NON-FUNCTIONAL ones — is a good analogy of the power of random variation and natural selection, which is premised on the origin of information by chance variation, and the selection of FUNCTION on superiority of some sub-populations.

    4 –> that was the heart of Sir Fred’s challenge and it is the heart of the design theory challenge to the claimed spontaneous origins of life and of novel body plans.

    So, the distraction on long answers etc was a misdirection form your own failures of selective half-truthful citation and/or summary, and failure to address the matter cogently on the merits, other than by denial in the teeth of patent facts [cf 11 below].
    Onlookers, the pattern is painfully clear.

    10] Creationists love to harp on about Darwin’s “racism” as though [if it were true] it invalidates everything else he has to say. But they don’t mention much about the astonishing sexism in some of Hoyle’s novels.

    In context, this is an instance of the “Design theory = Creationism in a cheap tuxedo promoting a hidden theocratic tyrannical agenda” slander by false association and falser accusation.

    Worse, the issue with Darwin and his racist social darwinism from say Ch 6 of his Descent of Man, is that it documents a start-pint for a HISTORICAL chain of causes,t hat ended up with eugenics, euthansaia of “undesirables,” and genocide. That is a part of the Darwin legacy that needs to be honestly faced, but is often dodged as just shown.

    And, Darwin’s scientific legacy stands or falls on its own merits.

    Darwinian mechanisms may account for some cases of micro-evolution, but – as for instance Behe’s empirical edge of evolution illustrates and the sudden appearances of phyla in the Cambrian fossil strata reveal — they have never adequately accounted for the macro-evolutionary changes required to turn a worm or primitive fish into us in about 600 mn years.

    As to Hoyle and novels (and claimed “sexism” therein), I have never hitherto heard of him as a novellist; I only have known of him as a major astrophysicist who keeps turning up in a lot of areas I have had interests in, and as a holder of a Nobel-equivalent prize.

    Prejudice based on sex is wrong, but respecting the differences of nature reflected in maleness and femaleness is right. (E.g. gentlemen use their generally superior physical strength to PROTECT women, and let ladies go first, save when the lion is coming.)

    11] The distance of a given letter sequence from the target in WEASEL is a model of a gene’s fitness to its environment. There fore it is “a good analogy of the power of random variation and natural selection, which is premised on the origin of information by chance variation, and the selection of FUNCTION on superiority of some sub-populations,” because that distance is the way we happen to modeling functionality.

    A model is of course an analogy.

    But in this case, selection of generational champions on mere increments in proximity to target of “mutant NONSENSE phrases” is plainly dis-analogous to a competition on FUNCTION that leads to domination of an overall population by “favoured races.” [Onlookers, this last is from the subtitle of Origin, from its earlier edns.]

    Worse, Dawkins admitted as much, as I already cited from BW:

    Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection . . . In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success.

    Of course, survival and a living organism and reproduction embed vast levels of information rich functionally specific complex information, starting in the 100′s of thousands of bits worth of DNA storage; for observed life. And, as I pointed out already, this is vastly beyond the 1,000 bit threshold where the entire resources of the observable universe could not credibly search more then 1 in 10^150 of the config space.

    That is, random search for required initial functionality-driving information is not a credible mechanism. And, until you achieve life function and reproduction – including the von Neumann replicator with blue print, code, reader and effectors – you cannot compete on relative function. Similarly, until a functional body plan exists, the level of evolution required to account for the 3 dozen or so phyla and sub-phyla in the Cambrian is not credible, esp. as we are now dealing with increments of 10′s – 100′s of m bits of required code based functional information.

    12] the first letter of sequence corresponds to length of the neck of the virtual creature . . .

    Until you have a credible basis to account for the origin of the relevant information to build a neck, you cannot use this.

    13] KF will probably regale you with his conspiracy theory about Lewontin and how evolution is all a materialist plot that depends on a material origin of life, which means OOL is relevant to everything, apparently. I suspect that if a step by step origin of life is ever established, KF will most likely say that it begs the question of where matter came from, and that that was the issue all along, and by concentrating on OOL we were simply distracting with clouds of oil of ad hominem burning straw men meant to poison and confuse …

    Onlookers, simply take a glance at my always linked.

    You will see that I start from the issue of information origination, then apply it in sequence to OOL, origin of body plan level biodiversity, and the issue of the fine-tuned functional complexity of the cosmos. All, on empirical evidence and reasoned argument linked thereto.

    I then point out — with relevant evidence adn tellign citations including that from Mr Lewontin that would be so deftly brushed aside [and ignoring the actions of the US National Academy of Sciences that show that in recent years, the attitude in the 1997 quote by a NAS member has become official policy, with demonstrably unjust consequences] — the impact of the neo-magisterium on origins science and science education, highlighting how the a priori imposition of evolutionary materialism censors science from being the unfettered (but ethically and intellectually responsible) pursuit of the empirically warranted truth about our world.

    The above, in short, is simply a jaundiced barbed dismissal that ducks addressing a cluster of evidence that seriously challenges the claims of the institutionally dominant materialism of our day. In a context where matters of basic justice are at stake.

    For shame!

    And given the pattern of sleazy rhetorical tactics I have had to expose overnight, that speaks volumes on the real balance of the matter on the merits.
    ______________

    All of this is ever so sad.

    But, to be forewarned is to be forearmed — if we are wise.

    GEM of TKI

  282. It seems pretty trivial to focus on getting the exact code that Dawkins wrote, it’s a throw-away example – that any ape with a keyboard can code up in an hour. I wrote it in C++ and it works without locking.

    To focus on the exact code that Dawkins used seems trivial, it serves no purpose other than to attack the man himself. The important thing is whether the code works and any ape with a keyboard and compiler can demonstratively show it to work.

  283. The issue here, at its core, is simple. Is the algorithm that Dembski and Marks describe the same as the one Dawkins describes.

    The answer, clearly: It is not.

    You have consistently failed to deal with this simple issue, resorting instead to verbal gymnastics to try and make it look like all the obvious differences between the two are not really differences, or are irrelevant to the point, and to making derogatory comments about the motivations of those who are questioning your dubious reasoning.

    Your profound inability to deal with these simple and straightforward issues is shocking, as is your contempt for academic standards. I see no point it continuing with this, you are beyond the grasp of reason, logic and evidence.

    Goodbye.

  284. BillB:

    The game just changed.

    After the red herring, strawman and ad hominem fest overnight, you have proved that you were a harbinger.

    What is indicated now is apology and correction on your part; and that of several others.

    On basic civility.

    Absent that, discussion is over.

    G’day.

    GEM of TKI

    PS: Onlookers Point 5 above answers to anything on the serious merits BillB might otherwise have had. (And of course the just above from him concludes with yet another turnabout false accusation. I think astute onlookers can easily enough see that others, Joseph and I have taken a lot of time and effort to answer to genuine issues on the merits, ever since December last. To slander us as distracting and distortion to try to reduce us to immoral equivalency to those whose sleaziness is revealed above through documented misdirection, misrepresentation and mischaracterisation, is slander, willful and malicious, inexcusable slander. Period. [Save, that this last slander tells us a lot of what we need to know about the real balance of the case on its merits.])

  285. 4,502 word salad. Yum.
    Is this a record, I wonder?

    kf waffles

    1] DNA-J, 265: …even if there were an explicit latching mechanism in Weasel[and all the evidence indicates that there is not one], that would not make it a partitioned search as described by D&M. The first reported Weasel run in TBW CANNOT be the result of a partitioned search. Only two letters change in generation 2.

    The essential point in partitioning, according to M & D [p. 1055], of course – from their example — is that “Two of the letters {E, S} are in the correct position . . . In partitioned search, our search for these letters is finished . . . “ (That is, a partitioned search is one that identifies correct letters individually and by one mechanism or another preserves them from reversion, so that he progress of the run of generational champions is ratcheted, with the successful letters being latched. Latching of coruse means: “To close or lock with or as if with a latch.”)

    Oh dear.
    We can agree that partitioned search, as accurately described by D&M in eqn22, latches.
    Unfortunately, you are using this fact to conclude that a (hypothetical) latching search is a partitioned search.

    All partitioned searches latch.
    Kf’s imagined Weasel latches.
    Therefore kf’s imagined Weasel is a partitioned search

    All ostriches have two legs
    Kf has two legs
    Therefore Kf is an ostrich.

    I don’t think so.

  286. kf waffles on

    3] DNA-J, 269: for partitioned search without sample replacement, the target can be found in N-1 queries (p1056) irrespective of the target length.

    The basic problem? Here is the M & D analysis of partitioned search in the IMMEDIATE context of Weasel, p. 1055:
    Assuming uniformity, the probability of successfully identi-fying a specified letter with sample replacement at least once in Q queries is 1 – (1 – 1/N)Q, and the probability of identifying all L characters in Q queries is
    q = (1 – (1 ? (1/N))^Q)^L . (22)
    Red herring led out to strawman again.

    I understand where you may have gotten confused, kariosfocus: D&M’s article is poorly written. Page 1055 describes the mathematics of a partitioned search with sample replacement, but the authors then slip (without indicating to the reader that they have switched algorithms in midstream) into describing in words the behavior of a partitioned search without sample replacement on p 1056, the page I cited.
    The misleading paragraph begins on p1055 “The enormous amount of active information provided by partitioned search is transparently evident when the alphabet is binary. Then, independent of L, convergence can always be performed in two steps.” Err, only without sample replacement. They go on to spend a whole paragraph discussing a partitioned search without sample replacement.
    (For onlookers who are playing with EIL WeaselWare, this second search algorithm is mathematically the same as the so-called “Deterministic Search”, and it performs much, much better than the “Partitioned Search”, which reduces its “Active Information” by deliberately ignoring useful information provided by the oracle.

  287. kf whines
    Worse, this is what I actually said about Mr Hoyle (and note the part that was conveniently omitted from the cite without even a ellipsis to warn the reader):

    Remember you are in the presence of a Nobel Prize equivalent holder here. he may be wrong on points, but he is not going to be making simplistic blunders, and even his errors will be instructive. That is my experience from many years of running across his work, on a wide array of topics, starting with the Steady State universe Hypothesis. (He it is who gave the name “big bang” to the cosmogenetic theory of that name, but he did not intend it to be a positive term.)

    In short, just the opposite to blind adherence to authority, I am saying that you need to treat competent workers with respect and highlighted how a major error of Sir Fred Hoyle – the Steady State theory – was highly instructive!
    Worse, this was suppressed and distorted by use of half-truthful selective citation in 271, which HAD to be deliberate. This is utterly inexcusable.

    kf is correct that I omitted the text that he bolded. But since I did not quote anything AFTER the Nobel Prize line, ellipsis seems unneccessary. I might as well fault kf for omitting the preceding sentence “And please resist the red herrings and strawmen in the usual rebuttals of Hoyle a la Wikipedia.” when he quoted me quoting him. What, no ellipsis, kairos??
    I omitted the sentence beginning “That is my experience…” because I was trying to avoid any implication that the “authority” kf was arguing from was himself, rather than Sir Fred. If I had been trying to quote-mine, I would have omitted the phrase “and even his errors will be instructive”, surely?

    In closing, I would like to thank kf for demonstrating that Weasel performs much better than a random search, and that mutation and selection can, cumulatively, produce results that appear directed/designed. That was, after all, CRD’s only point.
    I would also like to thank him for highlighting the sloppy writing seen in section E of the D&M paper. If someone as smart as kf did not notice the elision from Partitioned to Deterministic searches on pages 1055 – 1056, there is little hope that typical readers will be able to spot that eqn22 CANNOT describe a search that has generational champions, and therefore it CANNOT describe Weasel (irrespective of pseudo-quasi-implicit-latching).

  288. –kf
    Dembski and Marks start in their paper with the phrase:
    SCITAMROFN*IYRANOITULOVE*SAM
    I calculated a next generation using Dawkins’s algorithms with populations of 10,50 and 100 – and mutation rates of .04, .05 and .1. The tenth string in the list is the second generation given in the paper of Mark and Dembski. The differences with the first generation are in bold face:

    1. SCITAMROFN*IYRANOIEULOVE*SAM
    2. SCITAMROFN*IYRANOITULOGE*SAM
    3. ECITAMRI*N*IYZANOITULOVE*SAM
    4. SCITAMROFN*IYRANOITUL*VE*SAM
    5. SCITAMROFN*IYRANOITULOVE*SEM
    6. SCITAMOOLNOIYRAMOITULOVE*SEM
    7. SCITANROFN*IYYANOITULOVE*SAM
    8. SCITIMROFN*JYRANOITULOVE*SAM
    9. SCITAMROFN*ICRHNOITSLOWE*SAV
    10. OOT*DENGISEDESEHT*ERA*NETSIL

    Can you spot a difference in the design of the strings? And for latching

  289. KF @ 279:

    “3] Weasel also shows cumulative selection, which was showcased by a the “famous” 1986 runs that showcased how the progress to target in the sampled runs is without reversion.”

    Question for KF: Have you EVER seen a complete printout of a run of Dawkin’s Weasel program?

  290. Onlookers:

    It is sadly plain that the assorted Darwinists above simply do not understand the lines they have now collectively crossed, Nor do they seem to understand that the real issue is now whether they are willing to acknowledge serious error and return to civil conduct.

    As to the further reiterations of misdirecting, misrepresenting and mischaracterising, polarising arguments above, they have all been long since answered repeatedly and cogently in details above and in onward linked materials.

    (Darwinists often seem to think that by trumpeting specious claims loudly enough, long enough and long enough, they will prevail. All they succeed in doing here at UD is demonstrating the puerility of both rhetoric and attitude. But, sadly, in the wider public, such self-discrediting and destructive behaviour may not be recognised for what it is and where it too often leads if uncorrected and unchecked.)

    I will simply briefly note on points for the sake of reminder and record, for those who came in late:

    1] DNA-J, 285: We can agree that partitioned search, as accurately described by D&M in eqn22, latches. Unfortunately, you are using this fact to conclude that a (hypothetical) latching search is a partitioned search.

    Partitioned searches ratchet to the target and part of that ratcheting is latching of already successful letters – as has been plain from the very beginning of the discussion. Latching – implicit or explicit –is a reliable sign of ratcheting action and so of partitioning. (But then, Darwinists seem to have basic problems with inferring based on empirical signs.)

    2] DNA-J, 286: Page 1055 describes the mathematics of a partitioned search with sample replacement, but the authors then slip (without indicating to the reader that they have switched algorithms in midstream) into describing in words the behavior of a partitioned search without sample replacement on p 1056, the page I cited.

    The analysis relevant to Weasel is that on 1055 leading up to Eqn 22, as was pointed out correctively above. What is discussed later on 1056 is another case, which has been dragged across the discussion as a red herring.

    3] DNA-J, 287: kf whines . . . . kf is correct that I omitted the text that he bolded. But since I did not quote anything AFTER the Nobel Prize line, ellipsis seems unneccessary.

    As can be seen from what is now point 7 in 280 above, by omitting what followed, D-J materially misrepresented what I said, twisting my words into a blind appeal to authority, when in fact – as the suppressed example of the Steady State theory showed – I was pointing out that even the errors of someone like Hoyle are instructive. (One cannot simultaneously be talking about learning from the errors of great thinkers while appealing to blind adherence to them!)

    4] I would like to thank kf for demonstrating that Weasel performs much better than a random search, and that mutation and selection can, cumulatively, produce results that appear directed/designed. That was, after all, CRD’s only point.

    D-J here neatly omits WHY Weasel outperforms random search: it is targetted search with an already built in target that uses warmer-colder proximity to target metrics to reward “nonsense” — i.e. non-functional – phrases. In short, Weasel is an example of intelligent design and the power of active information.

    And, CRD’s intent was plainly to give the impression that his ‘cumulative selection” was a good analogy for random variation and natural selection based on differences in functional performance. Dawkins had to admit that Weasel is fundamentally dis-analogous, but seems to have relied on the difference in rhetorical impact of a spectacular simulation and qualifying weasel words that point out that there is more to the simulation than meets the eye.

    This is manipulation, not education.

    5] Dieb on runs, generations and latching

    Implicit latching is of course demonstrated, and the abstract possibility of slippage – which has been discussed, is irrelevant to the fact that good “tuned” runs do show latching of the generational champions.

    That is all that is required to explain the apparent latching effect in the SHOWCASED 1986 runs.

    6] DJM, 289: Question for KF: Have you EVER seen a complete printout of a run of Dawkin’s Weasel program?

    Have you?

    Have you got the code to demonstrate what the program actually did as opposed to inference to best explanation on its behaviour?

    More directly, the following is what I had to say, without clipping off conveniently:

    3] Weasel also shows cumulative selection, which was showcased by a the “famous” 1986 runs that showcased how the progress to target in the sampled runs is without reversion. (This is consistent with the basic, plain garden untwisted meaning of “cumulative” [i.e. I here cite Dawkins -- KF]: Increasing or enlarging by successive addition. A sense that we have every reason to see from his descriptions and examples as the one intended by Mr Dawkins c 1986 in BW; latterday “revisionising” notwithstanding.)

    4] two mechanisms have been shown — yes, SHOWN — capable of producing runs of generational champions that produce the same effect: (i) ratcheting action based on explicit latching of successful letters to date in Weasel, and (ii) ratcheting action produced by implicit latching due to interaction between selected population sizer per generation, mutation rate per letter and selection filter characteristics.

    5] Mr Dawkins has more or less has said that the actual code for Weasel c 1986 is not forthcoming, but the various algorithms and programs currently on the web are good enough to replicate the essential action, whch seems to have been implicit not explicit.

    Now, it is Mr Dawkins who described Weasel as showing “cumulative selection,” showcasing runs in 1986 that show that for over 200 places where such reversion could presumably occur, it never happens once. (And that in a context where we easily see how incorrect letters often persist for decades of generations.)

    So, we have good reason to infer that for good runs, Weasel c 1986 did ratchet to target, and in so doing effectively locked up already correct letters in genrational champions. The only question on this secondary point is whether implicitly or explicitly.

    And BOTH mechanisms have been demonstrated.

    On Mr Dawkins statements as reported since about 2000, it is believed that Weasel 1986 latched letters in the generational champions implicitly.

    +++++++++

    Again, we see the same saddening pattern of misdirection, misrepresentation and mischaracterisation.

    We have been warned on what is happening and what its consequences are likely to be if we let Darwinists get away with such uncivil and misleading or outright deceptive tactics.

    GEM of TKI

  291. –kf
    you made me smile: Darwinists often seem to think that by trumpeting specious claims loudly enough, long enough and long enough, they will prevail.
    Long enough and long enough, that’s us Darwinists. But seriously, I asked:
    Can you spot the difference in design in the following ten strings? Can you explain the difference?

    1. SCITAMROFN*IYRANOIEULOVE*SAM
    2. SCITAMROFN*IYRANOITULOGE*SAM
    3. ECITAMRI*N*IYZANOITULOVE*SAM
    4. SCITAMROFN*IYRANOITUL*VE*SAM
    5. SCITAMROFN*IYRANOITULOVE*SEM
    6. SCITAMOOLNOIYRAMOITULOVE*SEM
    7. SCITANROFN*IYYANOITULOVE*SAM
    8. SCITIMROFN*JYRANOITULOVE*SAM
    9. SCITAMROFN*ICRHNOITSLOWE*SAV
    10. OOT*DENGISEDESEHT*ERA*NETSIL

  292. Kairosfocus, you are as enjoyable as ever.

    2] DNA-J, 286: Page 1055 describes the mathematics of a partitioned search with sample replacement, but the authors then slip (without indicating to the reader that they have switched algorithms in midstream) into describing in words the behavior of a partitioned search without sample replacement on p 1056, the page I cited.

    The analysis relevant to Weasel is that on 1055 leading up to Eqn 22, as was pointed out correctively above. What is discussed later on 1056 is another case, which has been dragged across the discussion as a red herring.

    Interesting. Please show me where D&M indicate that they are now talking about a different algorithm. Why do they include it in the paper, if it is such a red herring?
    Let’s take a quick look at the original post that kf was “refuting”:

    DNA Jock at 269:
    Joseph, I understand that you are going for the second door:
    “A latching process is (necessarily) a partitioned search (as modeled in eqn22)”
    which is a much better choice than the third door:
    “Weasel is a partitioned search (as modeled in eqn22)”, which is blatantly wrong.

    The key aspect of the partitioned search is that it is a “divide and conquer” procedure(p1055), in which the search for each character is independent of the search for the other characters. Thus for partitioned search without sample replacement, the target can be found in N-1 queries (p1056) irrespective of the target length. There are whole categories of search algorithms that work by step-wise comparing a short search string (one or two letters) with the target (starting at one end and moving along until a match is found.) This information is then used to infer the FOO (p1054) for the target, and subsequent short search strings use the derived FOO. Useful if the FOO is unknown.
    It latches, but it ain’t a partitioned search

    I am merely referring to a particular type of partitioned search, as described by D&M. I am not claiming that they think it describes Weasel (although they may well leave unsophisticated readers with that impression). I certainly don’t think it describes Weasel. So where’s the beef?
    Furthermore, given that kf had clearly read this post, and therefore been introduced to the idea of a algorithm that latches but is not a partitioned search (as described by eqn22), I find his continued efforts to assert “latches, therefore partitioned” hilarious.

    I point to his undistributed middle, thus:

    All partitioned searches latch.
    Kf’s imagined Weasel latches.
    Therefore kf’s imagined Weasel is a partitioned search

    All ostriches have two legs
    Kf has two legs
    Therefore Kf is an ostrich.

    I don’t think so.

    And his response is to merely repeat his fallacy:

    Partitioned searches ratchet to the target and part of that ratcheting is latching of already successful letters – as has been plain from the very beginning of the discussion. Latching – implicit or explicit –is a reliable sign of ratcheting action and so of partitioning. (But then, Darwinists seem to have basic problems with inferring based on empirical signs.)

    Maybe I was wrong about the bird.

    As to the further reiterations of misdirecting, misrepresenting and mischaracterising, polarising arguments above, they have all been long since answered repeatedly and cogently in details above and in onward linked materials.

    (Darwinists often seem to think that by trumpeting specious claims loudly enough, long enough and long enough, they will prevail. All they succeed in doing here at UD is demonstrating the puerility of both rhetoric and attitude. But, sadly, in the wider public, such self-discrediting and destructive behaviour may not be recognised for what it is and where it too often leads if uncorrected and unchecked.)

    Say no more.

    In closing, I would like to thank kf for demonstrating that Weasel performs much better than a random search, and that mutation and selection can, cumulatively, produce results that appear directed/designed. That was, after all, CRD’s only point.
    I would also like to thank him for highlighting the sloppy writing seen in section E of the D&M paper. If someone as smart as kf did not notice the elision from Partitioned to Deterministic searches on pages 1055 – 1056, there is little hope that typical readers will be able to spot that eqn22 CANNOT describe a search that has generational champions, and therefore it CANNOT describe Weasel (irrespective of pseudo-quasi-implicit-latching).

  293. DNA_Jock, good observation @ 286. It also highlights the inaccuracy of referring to active info as a measure of problem-specific information. A search without replacement is based on the same problem-specific information as a search with replacement, and yet the active information measure of the former is higher. The active information measure is a function not only of the information available, but also of the way that information is used.

  294. Onlookers:

    Look at the above.

    Do we really want to cede more and more institutional and policy power in science, education the courtroom and the parliament to men who behave like the above, or who tolerate and defend behaviour like this — an excerpt from Mr Dawkins’ latest book?

    (For those who need a 101: planets orbiting the sun is a direct, current observation. The holocaust is copiously documented [cf the records of the trials of the major war criminals which should still be accessible at major libraries] eyewitness lifetime [my parents are still alive] history, denied only by Neo-Nazis and Islamist radicals or the like. In Europe people have been gaoled for holocaust denial.

    The — unobserved, unrecorded by us — alleged deep past origins of the cosmos, of life in it and of major body plans then man by claimed spontaneous forces tracing only to chance plus blind mechanical necessity is by contrast all too reminiscent of the tall tales of Baron Munchhausen pulling himself out of the primordial swamp by pulling on his bootstraps.

    When it is not playing at tyrannical [cf also here] neo-magisterium by the materialist high priesthood, as we have documented by Lewontin and now implemented by the US National Academy of Sciences and others.)

    To be forewarned is to be forearmed.

    G’day.

    GEM of TKI

    PS: On matters of substance I have just one supplemental footnote.

    It so happens that the Dembski-Marks calculation of probabilities in the IEEE paper p 1055 is based on the pattern of latching of letters once they go correct.

    (Contrast that with someone above who tried to drive a rhetorical wedge between ratcheting and latching. Instead, we may easily see that implicit latching is demonstrated and that once such latching of generational champions exists as the weasel “nonsense phrases” ratchet their way through targetted, proximity — not functionality — based “cumulative selection” filtering, then the analysis applies.)

    With double force, we see that Weasel’s headlined and trumpeted “success” of getting to target much faster than a random walk would, is based on the built in active information manifested in the targetting and the proximity-based hotter-colder filtering and promotion. As Dawkins admitted in 1986, Weasel builds in the required complex coded functional information to begin with [as the target], so it cannot reasonably be used as a good analogy of a process that is claimed to originate de novo complex functionally specific coded information.

    And to pretend otherwise is simply and plainly to reduce one’s reasoning to question-begging absurdity.

  295. PPS: Implicit latching, as noted and liked ever so many times in recent days, has long since been DEMONSTRATED, in the context of ratcheting, cumulative progress to target of nonsense phrases. And so we have a viable mechanism fro explaining the evident cumulative progressing, ratcheting latching action from the Weasel 1986 showcased o/p’s. Therefore we can nail the stake through the heart of the Darwinist attempt to dismiss latching, as a distraction from the root problem of fundamental dis-analogy between targeted search on mere proximity and the need to actually originate complex functional information by chance plus blind necessity; in the teeth of the massively substantiated — and Internet full of FSCI is exhibit no 1 — observation that FSCI is only credibly produced by intelligence. Which Darwinists, plainly, would rather not discuss.

  296. kairosfocus @ 290:

    “6] DJM, 289: Question for KF: Have you EVER seen a complete printout of a run of Dawkin’s Weasel program?

    KF: Have you? ”

    I’ll take that as a “No” and ignore the 400 following words which don’t answer my question.

    So you have never once seen a complete run of Dawkins Weasel program and consequently have no evidence to think that it lataches whatsoever beyond your own inability to comprehend the purpose of the program or the phenomena it illustrates. Yet you slag Dawkins and call him dishonest!

    Talk about “soaked in oil of ad hominem!”

  297. –kf,
    I understand your last post that you see no difference in the design of the following ten strings:
    1. SCITAMROFN*IYRANOIEULOVE*SAM
    2. SCITAMROFN*IYRANOITULOGE*SAM
    3. ECITAMRI*N*IYZANOITULOVE*SAM
    4. SCITAMROFN*IYRANOITUL*VE*SAM
    5. SCITAMROFN*IYRANOITULOVE*SEM
    6. SCITAMOOLNOIYRAMOITULOVE*SEM
    7. SCITANROFN*IYYANOITULOVE*SAM
    8. SCITIMROFN*JYRANOITULOVE*SAM
    9. SCITAMROFN*ICRHNOITSLOWE*SAV
    10. OOT*DENGISEDESEHT*ERA*NETSIL

  298. You are heading a bit off-topic, Kairosfocus, but thanks for some great links.

    Two minor quibbles:
    You said:

    (Contrast that with someone above who tried to drive a rhetorical wedge between ratcheting and latching.

    Now, if you were referring to me, then you are just making stuff up.

    So I am guessing that you were referring to BillB at 270 (citations should be specific and appropriate, btw)

    Joseph:

    Latching individual letters is a partitioned search, ratcheting towards a target is only a partitioned search if individual letters are locked out of the search when they reach their target.

    Partitioning means to divide up the search into separate, independent units. WEASEL is not an algorithm that searches for individual letters, it is not partitioned.

    But BillB’s first paragraph was a response to Joseph’s Humpty-Dumpty attempts to re-define the word “cumulative”, so he is trying to employ Joseph’s lexicon. I would be happy if we could agree to use one of the “latching”/”ratcheting” pair to refer to mechanisms, and the other to refer to behaviors, but when I tried to make this behavior/mechanism distinction, you promptly re-defined the word “mechanism”.
    Rhetorical wedge, indeed.
    BillB’s second paragraph sums up the entire issue at hand in only 25 words. Brevity is the soul of wit.
    Ironically D&M discuss a Weasel algorithm (in a rather hand-waving manner) in Section F of their paper. Ooops.
    Second quibble:
    I have a better FSCI link for you. Tons of stuff there, actually.

  299. 299

    Hark! I have been accused of being a “Darwinist”; a baseless and unfounded slur for which not a shred of evidence has been provided. Shall an apology be forthcoming?

    Moving on.

    KF offers examples of latching and claims this as implicit latching, but is unable to offer a clear definition of implicit latching that I can detect (1). A demonstration of implicit latching is not a definition, and a claim that it is would be circular logic.

    I suggest this definition of implicit latching:

    Implicit latching occurs when the probability of advancing up the search gradient is strictly greater than the probability of regressing down the gradient.

    This definition should enable the behavior which you call implicit latching. It is also a fundamental property of all search algorithms (2). As such, implicit latching is a trivial property of all searches (2), and a useless definition.

    KF: What is your definition of implicit latching? Please explain how latching (explicit, implicit, quasi, any form) is not a property of all search algorithms (2).

    (1) I could have missed it, as there was an awful lot to sort through.
    (2) All search algorithms other than blind random search. I’m tired of typing this bit over and over.

  300. Sorry, I ducked out for a while because, well, I have a life.

    Yes, Gaz, I used read Private Eye many moons ago.

    I have one question for kairofocus that requires a yes/no answer. Let’s see if he can answer it in fewer than 1000 words.

    As we know, the implicit “latching” in WEASEL is dependent on the parameters of the algorithm. It’s very easy to make it not latch simply by choosing a suitably high p(mutation), or a low n(offspring). Thus “latching” isn’t central to the algorithm, but a side-effect of its operation when run with certain parameters.

    On the other hand, in the Dembski algorithm, latching is an explicit and central part of the algorithm itself. No change to input parameters to the program will cause it not to exhibit latching, because it’s hard-coded to do so.

    So my question is: in the light of this, do you think that there is any substantial semantic equivalency between the two algorithms?

    (As an aside, if you implement my suggestion of several messages and alter the target phrase slightly in each generation, the WEASEL algorithm would continue to work and converge on the (moving) target, whereas the Demski algorithm would totally fail because it’s already latched into place values that might change in subsequent generations. I wonder which one more closely models the process of natural selection?)

  301. Onlookers:

    The idea hitman games, lamentably, continue.

    I therefore first draw your attention to the always linked, App 7, in which the core issues were addressed step by step dating to April last.

    Similarly, observe the pattern of corrected Darwinist errors and uncivil tactics in 279 – 81 above.

    In short, were the objectors above really concerned to be accurate, balanced and fair, they have more than adequate materials to engage on the merits. But, sadly, we are quite plainly dealing with the rhetoric of distraction, misrepresentation and mischaractersation intended to poison the atmosphere of civil discussion, and to enable oppressive misbehaviour; as has been highlighted with all too many cases in point above.

    Also, while — sadly — to many of the commenters above have by indulgence in incivility and/or enabling behaviour for oppressive misconduct, have moved beyond the pale of civil discussion on the merits of a serious matter, it is about time we do another point by point cleanup on the record, addressing some of the grosser fallacies and agit-prop tactics, as a further 101.

    Of course this is at the risk of dismissive rhetoric about “word salads” etc – which simply proves that there is plainly no intent to engage on the merits cogently to wards a true and fair result, only to distract, distort, demonise and dismiss.

    But, for the record, starting with the main current objection:

    1] DJM, 296: So you have never once seen a complete run of Dawkins Weasel program and consequently have no evidence to think that it latches whatsoever beyond your own inability to comprehend the purpose of the program or the phenomena it illustrates.

    This is another case of brassy pounding repetition to create the false impression of truth: “Don’t believe yer lyin eyez and the dictionary.”

    For, the relevant showcased 1986 runs of Weasel’s generational proximity to target champions – as has been reproduced above and as has been in App 7 all along – are (from BW and NewScientist):

    ______________

    >>  1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL

     1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL >>
    ______________

    It is easy to directly observe that for over 200+ letters that could easily revert to incorrect status, were the “there is no credibly observable latching effect” claim true, WE NEVER SEE A SINGLE CASE OF REVERSION. That, from a sample of 300+ relevant letters, and in a context where there are many cases of incorrect letters persisting for decades of generations of champions.
    So, on good runs of Weasel, c 1986, such reversions are at least rare enough to not be easily observable – indeed, they are not observed at all in the actual evidence to be accounted for; that is, in the sense to be further described, showcased Weasel runs of generational proximity to target champions, c. 1986, evidently and observably ratcheted towards the target and latched correct letters in so doing. (All that is required to see that is to accept that one normally showcases typical but “good” behaviour of results in scientific and similar work.)

    And, the latching effect is precisely the observation that when a letter goes correct, it stays that way all the way home to the target, even as in successive generations, Weasel finds further letters to lock in as on target. Creating the ratcheting action with cumulative – AmhD: “Increasing or enlarging by successive addition” — progress to the target.

    Nor is this just a matter of our observation of the published results in two different venues.

    For, here is how Mr Dawkins enthusiastically described Weasel’s action, in BW:
    ____________
    >> It . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. ,i>The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed . . . . >>
    _______________

    CRD here speaks explicitly about cumulative selection, rewarding slightest increment to target, and contrasts the progress of non-functional nonsense phrases through targetted search with the effects that a random walk that would have to first meet a threshold of reasonable functionality before being rewarded with generational champion status, would have.

    In short, by words and examples, CRD makes it plain that latching, ratcheted action is the simplest and clearest sense of his language; consistent with the showcased outputs.

    (And, it has been demonstrated that such ratcheting, latched action can be achieved by two basic mechanisms – AmHD: 3. An instrument or a process, physical or mental, by which something is done or comes into being — explicit latching and implicit. There has been an attempt to try to define that the former is the only correct sense of the term so that references to latching or ratcheting distort what Dawkins showcased and gushed over in 1986. But of course a term that describes an observable effect is not something one can game around rhetorically like that, on pain of the absurdity of “Don’t believe yer lyin eyez.” [Latching is a description of an output pattern in the letters of runs of generational champions, and it is demonstrated that this effect occurs, as well as that it can be achieved by explicit code or implicit matching of parameters: generation size and mutation rate coupled to proximity to target filter characteristics.])

    The real reason this has subsequently become “controversial” is that the latching ratcheted action as nonsense phrases creep in to the target vividly reveals the fundamental dis-analogy between Weasel and the claimed power and mechanism of random variation and natural selection based on improved functional fitness.

    Worse, as Marks and Dembski demonstrated, once we see ratcheting-latching so that a correctly guessed letter does not in practice revert, for a good run, a fairly simple probability analysis obtains, which leads to the simple deduction of the advantage conferred by the active information embedded in the targetting and artificial selection on mere proximity of non-functional phrases confers.

    2] DJM, you slag Dawkins and call him dishonest!

    Actually, I have not called Mr Dawkins “dishonest.”

    I have instead repeatedly drawn attention to his writings in BW, and in particular the implications of the further words in his comments on Weasel’s action in BW, as has again been immediately accessible all along in App 7 the always linked and as has been pointed out step by step many times in various UD comment threads:
    ______________

    >> Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection, although human vanity cherishes the absurd notion that our species is the final goal of evolution. In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success. [TBW, Ch 3, as cited by Wikipedia, various emphases added.] >>
    ______________

    These words make it plain that at the time of publication, CRD knew that Weasel’s artificial cumulative selection of non-functional “mutant nonsense phrases” on resemblance to a distant ideal target was fundamentally dis-analogous to the claimed ability of random variation and natural selection on superiority of biological function.

    That is why he had to acknowledge that it was misleading in important ways.”

    And it is a plain duty of care of the educator – public or otherwise – not to mislead.

    More specifically, Weasel works to gain an advantage over a random walk reference base because it pre-loads a target and then rewards hooter-colder guesses, without reference to reasonable thresholds of complex function. And, it was precisely the need to achieve bio-function and improvements in bio-function, with all the implied complexity, that was at the heart of the background to Weasel: the challenge raised by Sir Fred Hoyle and by others going back to Schutzenberger and others at the famous Wistar consultation at the top level, of 1966, on the challenges to get to complex function in initial and novel biological systems.
    In short, Weasel begged the question at stake in a misleading way. And, even the qualifying – aka “weasel” [this might have something to do with the very phrase chosen as target . . . ] — words cited above exploit a yet subtler rhetorical effect: the headlined, spectacular simulation grabs and focusses attention, but the qualifications will be easily and generally – predictably – overlooked.

    (Just as a misleading headline often smears a person, but few ever read the qualifications and corrections buried deep in the story or on a back page a few days later.)

    Currently as well, the Marks-Dembski analysis on active information and its role explains the performance gain of Weasel over random walks amidst large configuration spaces with islands of code-based complex functionality.

    Again, it is the duty of educators to not mislead.

    So, this tactic by DJM, regrettably, is plainly a case of turnabout (“he hit back first . . .”)accusation.

    [ . . . ]

  302. ] DJM: Talk about “soaked in oil of ad hominem!” Turnabout, unwarranted [cf the discussion just above], immoral equivalency accusation. Sad.

    4] DIEB, 297: I understand your last post that you see no difference in the design of the following ten strings:

    I have of course focussed my discussion on the Weasel 1986 runs of generational champions as discussed at 1 above again. I have had no good reason to debate resemblances or non-resemblances among the strings listed by Dieb, which at best are distractingly irrelevant. (The strings we need to discuss are reproduced at 1 above, Dieb.)

    I have also shown why (most recently from 279 on) it is that on p. 1055 of the IEEE paper, it is proper to conclude that Dembski and Marks used a didactic illustration of what ratcheting-latching action is like — with a link to BW that gives the real-world run in view! — which then led up to the analysis of probability on the observation of latching. And latching of successful letters in the runs of generational champions, of course, can be achieved explicitly or implicitly; as has been demonstrated.
    This has been twisted into a strawmannish “algorithm” that would not be feasible of contruction. All, to support the claim that M & D distorted what Dawkins presented in his example and discussion of Weasel c. 1986.

    Here is the relevant section of the IEEE paper, again:
    __________________

    >> E. Partitioned Search

    Partitioned search [12] is a “divide and conquer” procedure best introduced by example. Consider the L =28 character phrase
    METHINKS ? IT ? IS ? LIKE ? A ? WEASEL. (19)
    Suppose that the result of our first query of L =28 charac-ters is
    SCITAMROFN ? IYRANOITULOVE ? SAM. (20)
    Two of the letters {E, S} are in the correct position. They are shown in a bold font. In partitioned search, our search for these letters is finished. For the incorrect letters, we select 26 new letters and obtain
    OOT ? DENGISEDESEHT ? ERA?NETSIL. (21)
    Five new letters are found, bringing the cumulative tally of discovered characters to {T, S,E, ?,E, S,L}. All seven char-acters are ratcheted into place. The 19 new letters are chosen, and the process is repeated until the entire target phrase is found.
    Assuming uniformity, the probability of successfully identi-fying a speci?ed letter with sample replacement at least once in Q queries is 1 – (1 – 1/N)^Q, and the probability of identifying all L characters in Q queries is
    q = (1 – (1 – (1/N))^Q)^L. (22) >>
    ______________________

    Notice, first, the explicit context of explanation by didactic example, as opposed to presentation of a realistic algorithm and output data from such.

    Here, it is obviously not practically feasible to have a single member per generation case that varies 26 letters and is sufficiently likely to be observable, to get 5 new letters at one go. Instead we would be looking at a very large population of mutants per generation with an aggressive filter that will pick up far tail of distribution effects such as multiple letters going correct that can see a case of 5 letters going correct.

    Such would be functionally equivalent to the more realistic case of multiple intervening generations, with the highlighted characteristic: “[once a cluster of letters goes correct in the champions] our search for these letters is finished.” That is, latching of correct letters and ratcheting progress to target. And, credibly, that is what the linked discussion in BW is about, as we may see from 1 above.

    How can such latching of correct letters in generational champions be accomplished? Ans: in two ways, explicitly or implicitly.

    Once latching-ratcheting of the run of generational champions is present, and with number of Queries being seen as number of mutants to date, the probability analysis follows trivially. Just, we should note that Q will jump in clusters associated with G generations of size S.
    Of course, I do not expect those determined to take as suspicious as possible an interpretation of the Marks-Dembski paper will find this convincing.

    I only aim to show that such are being unreasonable and selectivley hyperskeptical, especially by contrast with the degree of charity they wish us to give to Mr Dawkins, who has said in so many words that his presentation of Weasel and its results is “misleading in important ways.”

    5] DNA-J, 298: if you were referring to me, then you are just making stuff up. [This on my remarks that someone was trying to “drive a rhetorical wedge between ratcheting and latching”]

    In short, I am being accused of making false accusations. However, a scrollup will show that a primary reference is e.g. DNA-J, 285:

    Oh dear.

    We can agree that partitioned search, as accurately described by D&M in eqn22, latches.
    Unfortunately, you are using this fact to conclude that a (hypothetical) latching search is a partitioned search.

    All partitioned searches latch.
    Kf’s imagined Weasel latches.
    Therefore kf’s imagined Weasel is a partitioned search

    But, instead of this strawman and red herring muddles on undistributed middles etc, the defining characteristic of partitioning of search as just highlighted, as used by Marks and Dembski, is that correct letters are latched and ratcheting progress builds on what is achieved by making successive additions of correct letters through searching, until the whole target is cumulatively achieved. And, I am taking “partitioning” in the light of that usage, whatever other uses there may be in other contexts.

    Worse, as we may see from the mathematical probability analysis above, the factor that is used to deduce the results in Eqn 22 is that such searches latch successful letters so that once achieved the letter stays locked in: catch and keep, not catch and release.

    That is why we may see that the probability of a given letter being correct in Q tries is (1 – [1 – 1/N]^Q), with N possible letter-states and assumed flat random distribution of guesses:

    –> probability of guessing a given letter correctly in any one throw are 1/N.
    –> probability of missing the letter on that throw is 1 – 1/N
    –> that of missing it all of Q times become 1 – 1/N]^Q
    –> So that of catching it on any one of the tries in the Q tries is 1 – [1 – 1/N]^Q)
    –> this builds int eh implication that once captured a letter does not slip back out again, i.e it is latched.
    –> Eqn 22 just extends this to a phrase of length L letters, on the assumption of probabilistic independence; and with the “no catch and release” rule in effect, we will see both latching and ratcheting action in the run of generational champions

    As long since described and repeatedly explained and demonstrated, this latching-ratcheting result can be achieved explicitly or implicitly. It is also credibly what we see in the results showcased for Weasel 1986.

    6] DNA-J: BillB’s first paragraph was a response to Joseph’s Humpty-Dumpty attempts to re-define the word “cumulative” . . . I would be happy if we could agree to use one of the “latching”/”ratcheting” pair to refer to mechanisms, and the other to refer to behaviors, but when I tried to make this behavior/mechanism distinction, you promptly re-defined the word “mechanism”.

    Turnabout accusation.

    First, as point 1 above for today shows, latching and ratcheting and cumulartive selection have a very particular context in which it is plain that not only modern recreations of Weasel ratchet and latch the o/ps [through mechanisms that are explicit and implicit, but credibly so did the generational champion runs showcased by CRD in BW and New Scientist in 1986.

    That is an important datum line.
    Next, cumulative has a plain meaning and in the context of the showcased runs that is the most natural meaning. If CRD had meant to say that Weasel showed slippages, he sure picked a peculiar way to say so!
    Nor is it a question-begging after the fact redefinition attempt to point out that

    a] AT ISSUE: mechanism has to do with the means by which a result is achieved, here cumulative, no slip-back ratcheting-latching action as may be observed definitively from modern recreations of Weasel, and on the preponderance of evidence for the 1986 runs as enthused over and showcased by CRD; cf. Point 1 above.

    b] EPISTEMOLOGICAL FOUNDATION: We are discussing an inference to the best explanation on the empirical data of the showcased weasel runs c 1986, and we are also discussing a program that implements a simulation. (Much of science works by such empirically anchored inference to best explanation.)

    c] DECISIVE POINT: the observed o/p results of the program – runs of generational champions — are produced by the behaviour of the program, which in turn is determined by its mechanisms and how it therefore takes in inputs [parameter settings, filter characteristics, original random letter seed] and processes such.

    d] ROLE OF UNDERLYING MECHANISM: It does so by creating mutant generations of a set size on a set per letter mutation rate, filtering on mere proximity to target and picking the nearest to date to become the next seed till the final champion hits home.

    e] ALTERNATIVE MECHANISMS: In so doing – as demonstrated — latching and ratcheting o/p results and associated behaviour can turn up based on explicit processing mechanisms, or implicit processing mechanism that rely on the interaction of the input parameters and the filter.

    And, in a context of confusion at best driven by misunderstandings leading to misrepresentations, being explicit and precise is far more important than being brief.

    [ . . . ]

  303. 7] I have a better FSCI link for you

    We need not bother with the hurled elephant tactic of a glitteringly general claim based on a substantially irrelevant literature bluff and dump, as the first article by Hazen – as discussed several times at UD — suffices to show what is going on.

    Excerpting, starting with the opening words:
    ____________

    >> Complex emergent systems, in which interactions among numer-ous components or ‘‘agents’’ produce patterns or behaviors not obtainable by individual components, are ubiquitous at every scale of the physical universe, for example in neural networks (1), turbulent fluids (2), insect colonies (3), and spiral galaxies (4). Complex systems also appear in a range of artificial symbolic contexts, including genetic algorithms (5), cellular automata (6), artificial life (7), and models of market economies (8) . . . . complex system. Furthermore, the ancient transition from a geochemical world to a living planet may be modeled as a sequence of emergent events, each of which increased the chemical complexity of the prebiotic world (9–11) . . . .
    The function of some emergent systems is obvious: a sequence of letters communicates a specific idea, a computer algorithm performs a specific computation, and an enzyme catalyzes at least one specific reaction. Less obvious are the functions of systems of many interacting inanimate particles, such as mole- cules, sand grains, or stars, but these systems may also be described quantitatively in terms of function, for example, in terms of their ability to dissipate energy or to maximize entropy production through patterning (e.g., refs. 26–29). Living systems, by contrast, typically display multiple essential functions (21, 30, 31). This consideration of complexity in terms of the function of a system, as opposed to some intrinsic measure of its patterning or structural intricacy, distinguishes our treatment from many previous efforts. >>
    ________________

    i –> Immediately, the article conflates complexity of order or even randomness with complexity of functional organisation; something that was wared against by Orgel all the way back to 1973:

    In brief, living organisms are distinguished by their specified complexity. Crystals are usually taken as the prototypes of simple well-specified structures, because they consist of a very large number of identical molecules packed together in a uniform way. Lumps of granite or random mixtures of polymers are examples of structures that are complex but not specified. The crystals fail to qualify as living because they lack complexity; the mixtures of polymers fail to qualify because they lack specificity. [Leslie Orgel (1973). The Origins of Life, p. 189 ]

    ii –> Similarly, Hazen fails to recognise at the outset characteristic distinctions between the actions of agents and those of chance and or necessity. That is, he is begging the question by failing to see that design is an empirically evident, characteristic and distinct phenomenon.

    iii –> Almost immediately thereafter, he fails to distinguish between a MODEL whose plausibility rests on the imposition of Lewontinain materialism on science, and the observational reality and challenges of getting form any plausible prebiotic geochemical environment and the organised, functional complexity of life.

    iv –> Along the way, he manges to assume – without providing a clear and balanced discussion of he evidentiary challenges and the real world frustrating empirical findings of OOL researches since 1953 — that there is a smooth pathway of small steps from simple chemicals to organised life forms which reproduce themselves using a von Neumann replicator: coded blueprint, code system with associated algorithms and data structures, reader, effector mechanisms.

    v –> He then diffuses the focused meaning of specific functionality by introducing dis-analogous cases: any old pile of sand will function as a pile of sand, but not any old string will function in a given context as a meaningful, code and information bearing functional entity that says something coherent or properly instructs the assembly of a protein’s amino acid sequences. And modest perturbation of the one will have but little effect: you still have a sand pile. For the other, modest perturbation destroys function, i.e we have sharply distinct islands of specific function. That is why the work of Abel, Trevors and others on functional sequence complexity and its quantification, is so important. (Cf my discussion of FSCI and related ideas here onlookers. Also cf the Weak Argument cor4ectives above.)

    8] TA, 299: I have been accused of being a “Darwinist”; a baseless and unfounded slur for which not a shred of evidence has been provided.

    If you choose to run with the wolves, you are hereby provisionally identified and treated as one of same. Sorry if you end up as a pet thats gets shot while running with the wolves. (Cf here, the current media trumpeted case of “civilians” taking gasoline from Taliban, who have just hijacked tankers and murdered the civilian crews.)

    9] KF offers examples of latching and claims this as implicit latching, but is unable to offer a clear definition of implicit latching that I can detect

    This has of course been given many, many times over, starting with the App 7 and being again given above:

    13 –> Letterwise partitioned search is also a very natural way to understand the Weasel o/p in light of Mr Dawkins’ cited remarks about cumulative selection and rewarding the slightest increment to target of mutant nonsense phrases. As such, it has long been and remains a legitimate interpretation of Weasel. However, on recently and indirectly received reports from Mr Dawkins, we are led to understand that he did not in fact explicitly latch the o/p of Weasel, but used a phrasewise search.

    14 –> Q: Can that be consistent with an evidently latched o/p?
    ANS: yes, for IMPLICIT latching is possible as well.  

    15 –> Namely, (i) the mutation rate per letter acts with (ii) the size of population per generation and (iii) the proximity to target filter to (iv) strongly select for champions that will preserve currently correct letters and/or add new ones, with sufficient probability that we will see a latched o/p. (This effect has in fact been demonstrated [the link here is the one I have been using all along] through runs of the EIL’s recreation of Weasel. [Link is to the development version of EIL Weasel with adjustable parameters])

    16 –> in a slightly weaker manifestation, the implicit mechanism will have more or less infrequent cases of letters that will revert to incorrect status; which has been termed implicit quasi-latching. This too has been demonstrated, and it occurs because an implicit latching mechanism is a probabilistic barrier not an absolute one. So, as the parameters are sufficiently detuned to make reversions occur, we will see quasi-latched cases.  Sometimes, under the same set of parameters, we will see some runs that latch and some that quasi-latch.

    Thus, BOTH latching and quasi latching have been defined long isnce in easily accessible materials, and that in terms of how they are achieved. In latching-ratcheting action, generational champions in a Weasel algorithm run have letters that once they go correct are subject to catch and keep [locked up pr latched – think of a panfish stringer with latching snaps here] not catch and release. That may be achieved explicitly or implicitly, as has been demonstrated.

    10] Nephmon, 300: in the Dembski algorithm, latching is an explicit and central part of the algorithm itself.

    Strawman.

    There is of course no “Dembski algorithm,” other than the cluster hosted by the EIL, which includes the explicitly latched and proximity search with adjustable parameters cases that will show latching implicitly under certain circumstances. (That is, once you show the reasonable reader behaviour that recognises a purely didactic illustration as opposed to presentation of an algorithm and its realistic output. This was already discussed above for today.)

    As to the idea that latching action is a mere side effect, the gushing comments of CRD as discussed above show that c. 1986, he did not regard this as a mere side effect but a remarkable achievement: “cumulative selection” — of non-functional mutant “nonsense phrases” on mere proximity to target — which beats mere “single step selection” — which requires achievement of reasonably complex function before selection on superiority of function — by millions and millions and millions of times over.

    11] As an aside, if you implement my suggestion of several messages and alter the target phrase slightly in each generation, the WEASEL algorithm would continue to work and converge on the (moving) target, whereas the Demski algorithm would totally fail because it’s already latched into place values that might change in subsequent generations

    Red herring led away to Strawman.

    What is to be explained is not something someone makes up for rhetorical purposes today, but he behaviour of Weasel c 1986, as showcased and thus also in absence of credible original code – the actual focus for this thread, onlookers – the behaviour of reasonable replicas thereof.

    Explicit latching is one reasonable reconstruction [on just the 1986 information], and implicit latching is another which becomes preferred if we reckon with the statements made by CRD and agents in the years since about 2000.
    _____________

    GEM of TKI

  304. I have had no good reason to debate resemblances or non-resemblances among the strings listed by Dieb, which at best are distractingly irrelevant.

    Well, ID is about the detection of design, therefore I’m not surprised that you have spotted a difference in the design of the strings below, and that it annoys you. Declaring it irrelevant won’t make it get away…
    1. SCITAMROFN*IYRANOIEULOVE*SAM
    2. SCITAMROFN*IYRANOITULOGE*SAM
    3. ECITAMRI*N*IYZANOITULOVE*SAM
    4. SCITAMROFN*IYRANOITUL*VE*SAM
    5. SCITAMROFN*IYRANOITULOVE*SEM
    6. SCITAMOOLNOIYRAMOITULOVE*SEM
    7. SCITANROFN*IYYANOITULOVE*SAM
    8. SCITIMROFN*JYRANOITULOVE*SAM
    9. SCITAMROFN*ICRHNOITSLOWE*SAV
    10. OOT*DENGISEDESEHT*ERA*NETSIL

  305. It takes a very special kind of person to simultaneously maintain that the opening pair:

    SCITAMROFN?IYRANOITULOVE?SAM. (20)
    OOT?DENGISEDESEHT?ERA?NETSIL. (21)

    is too “good” to be a real example, and is instead a “didactic example”, because it goes from 2 hits to 7 in one generation (Probability = 1 in 419, as previously pointed out to kf in post 164)

    Yet he continues to maintain:

    Here, it is obviously not practically feasible to have a single member per generation case that varies 26 letters and is sufficiently likely to be observable, to get 5 new letters at one go. Instead we would be looking at a very large population of mutants per generation with an aggressive filter that will pick up far tail of distribution effects such as multiple letters going correct that can see a case of 5 letters going correct.

    and

    I have also shown why (most recently from 279 on) it is that on p. 1055 of the IEEE paper, it is proper to conclude that Dembski and Marks used a didactic illustration of what ratcheting-latching action is like — with a link to BW that gives the real-world run in view!

    Unfortunately for kf, the first two generations in TBW are:

    WDL*MNLT*DTJBKWIRZREZLMQCO*P
    WDLTMNLT*DTJBSWIRZREZLMQCO*P

    Which only changes in two places, out of 25 incorrect letters. The probability that a partitioned search (as described by D&M) would do this is = 3.3 x 10^-31
    For those who dislike sceintific notation, that’s one in 2.9 million million million million million.

    So

    SCITAMROFN?IYRANOITULOVE?SAM. (20)
    OOT?DENGISEDESEHT?ERA?NETSIL. (21)

    Is too unlikely to be a real example, but

    WDL*MNLT*DTJBKWIRZREZLMQCO*P
    WDLTMNLT*DTJBSWIRZREZLMQCO*P

    Which is a trillion trillion times more unlikely, is just fine as an example.

    Note that the unusual behavior of generation 2 (given kf’s assumptions) was pointed out to kf in post (34), and many times since (190,199, etc).
    I even gave D&M the benefit of the doubt, allowing a mutation rate less than 100%. But you still cannot get a run that looks like the first run in TBW, using a partitioned search. (I did have fun though – the optimum occurs close to a 49% mutation rate – at which point generation #2 is fairly likely (1 in 32,471 runs), but the odds against finishing within 43 queries has grown to 1 in 23,992,787. So even with the generous assumption that these two are independent, we still have a probability of getting a partitioned search that changes 2 or fewer out of 25 at query two and hits within 43 queries = one in 0.7 million million. If we assume 2 minutes per weasel run, CRD would need to run a thousand computers continuously for nearly 3,000 years to get a partitioned search this weird.

    So I don’t think TBW is a good exemplar of the search described by equation 22.

    I will anticipate kf’s red herring: (remember that kf is maintaining that D&M were justified in citing TBW as an example of partitioned search, because of the behavior of the outputs), so any suggestion that CRD messed with the results would
    1) be an completely unfounded accusation of dishonesty
    2) concede our point that the citation is obviously inappropriate

    And now for a quick recap of the semantics battle –

    KF accuses me of “trying to drive a rhetorical wedge between latching and ratcheting”.
    I call him on this, saying

    if you were referring to me, then you are just making stuff up….ellipsis… I would be happy if we could agree to use one of the “latching”/”ratcheting” pair to refer to mechanisms, and the other to refer to behaviors, but when I tried to make this behavior/mechanism distinction, you promptly re-defined the word “mechanism”.

    [see footnote 1]

    To prove his point (that I drive a rhetorical wedge between ‘latching’ and ‘ratcheting’) he quotes my post highlighting his logical fallacy, which does not even contain the word ‘ratcheting’ :

    Oh dear.
    We can agree that partitioned search, as accurately described by D&M in eqn22, latches.
    Unfortunately, you are using this fact to conclude that a (hypothetical) latching search is a partitioned search.
    All partitioned searches latch.
    Kf’s imagined Weasel latches.
    Therefore kf’s imagined Weasel is a partitioned search

    (I went on to use the same fallacious logic to prove that kf is an ostrich, but no matter.)
    And then kf says :

    But, instead of this strawman and red herring muddles on undistributed middles etc, the defining characteristic of partitioning of search as just highlighted, as used by Marks and Dembski, is that correct letters are latched and ratcheting progress builds on what is achieved by making successive additions of correct letters through searching, until the whole target is cumulatively achieved. And, I am taking “partitioning” in the light of that usage, whatever other uses there may be in other contexts.

    All at once begging the question, and (brilliantly) re-defining the word “partitioning” (which has a specific mathematical meaning in D&M’s paper) to mean something entirely different. And thus, since HE thinks latching and partitioning are synonymns, any attempt to argue that there is a difference between them, or between mechanism and behavior, is “driving a rhetorical wedge between latching and ratcheting”, apparently.
    Note that kf has previously quoted from post 269, so we may assume that he read it and is therefore aware of the concept that a latching search may not be a partitioned search. Yet he continues to hammer away, repeatedly asserting what he knows to be a logical fallacy.
    So, in conclusion, it appears that anytime you lose an argument, kairosfocus, you invent totally novel meanings for words in order to avoid admitting defeat. ‘Mechanism’, ‘partitioning’, and the strictly telic use of ‘cumulative’.
    “Well, there’s glory for you” H.Dumpty
    BillB took 25 words to nail the issue at hand:

    Partitioning means to divide up the search into separate, independent units. WEASEL is not an algorithm that searches for individual letters, it is not partitioned.

    My own summary:

    D&M’s Eqn22 CANNOT describe a search that has generational champions, and therefore it CANNOT describe Weasel (irrespective of pseudo-quasi-implicit-latching)

    Foot Note 1: kf devised a novel definition for “mechanism” in his post 233 , which included this GEM:

    I firmly believe — on good grounds — that unless necessary causal factors are present an event CANNOT happen, and unless sufficient ones are present it WILL not happen. So if it happens, we can identify causal factors and how they work — i.e mechanisms. And given the issue of synergy — effects due to interaction — mechanisms do not have to be explicitly built and labelled as such. I do not believe in magical poofery!

    Reeeeally.

  306. DNA-J:

    Onlookers will be able to see that you have unfortunately distorted the matter, by comparing your remarks to mine in light of the cited section of the IEEE paper.

    I have pointed out in particular that it is a reasonable reading of the Dembski-Marks paper on p. 1055 that they intend to provide a brief tutorially oriented explanation, rather than realistic output of an algorithm. [Your remarks and too much of the above remind me of Kipling's poem If, and not happily.]

    Onlookers will be able to tell for themselves what is more reasonable.

    Having had to take up BL this morning already point by point, I will deal with your further remarks here anon.

    G’day.

    GEM of TKI

  307. I have pointed out in particular that it is a reasonable reading of the Dembski-Marks paper on p. 1055 that they intend to provide a brief tutorially oriented explanation, rather than realistic output of an algorithm.

    Isn’t that like gluing moths to trees – for tutorial reasons?

  308. Onlookers

    I have already had occasion to speak this morning to the turn that the blog has taken over the weekend, as we see the from Darwinist unresponsiveness to the responsibility issues that were addressed in the comments at 301 – 303 above.

    So, I will just link there (as done above), then call us back to footnotes on points that need a further remark or two, as I proposed to do yesterday:

    1] Dieb, 304: ID is about the detection of design, therefore I’m not surprised that you have spotted a difference in the design of the strings below, and that it annoys you. Declaring it irrelevant won’t make it get away…

    It seems I will only be able to get Dieb off this irrelvancy by being more detailed.

    The ten sequences selected of course are in part a run of a Weasel type program with reversions.

    Such is of course a distinct case that had Dieb troubled to read my App 7 the always linked, he would have seen explicitly addressed in point 16, where I discuss quasi-latching. (Having already linked demonstrated cases of implicit latching. Indeed, in the just linked thread form March-April, I then went on to give several runs that showed various other types of behaviour. All duly accessible and ignored in the haste to set up and knock over a strawman.)

    Beyond quasi-latching, there is also the – discussed as well — case where there is no apparent latching at all. And, it is explicitly the case that Weasel latches for “good runs” implicitly when the pop per gen, mut rate per letter and proximity to target filter interact to give that effect. Remember: DEMONSTRATED.

    Nowhere have I said that only explicit latching and implicit latching are possible. Just the opposite.

    Going further, the rhetorical point being made is that there is a Demsbki algorithm that is ever so distinct from the Dawkins algorithm, that it is a case of misrepresentation. But in fact the Marks-Dembski EIL, as already noted, hosts a GUI that gives a set of various Weasel algorithms, covering the bases for the various types and sub types that have been mostly discussed.

    Similarly, from the 1986 descriptions and showcased run excerpts the only thing we can see is that we can determine no one THE Dawkins algorithm. Explicit and implicit latching interpretations are reasonable on the evidence c 1986 [why there is a prize for actual credible code c 1986 – not forthcoming!], and we have no reason to immediately accept that the video runs of 1987 are the same algorithm as the one showcased in 1986. It is on subsequent reported statements c 2000 that it is held on balance of evidence that implicit ratcheting-latching is the likeliest explanation for the showcased behaviour c 1986, on which the 1987 video would be either a run of individual mutants or a detuned Weasel run that shows non-latched behaviour.

    All of which has been long since discussed and just as long since repeatedly ignored or distorted as inconvenient to the rhetorical agenda being pushed by the darwinists.

    2] DNA-J, 305: It takes a very special kind of person to simultaneously maintain that the opening pair:SCITAMROFN?IYRANOITULOVE?SAM. (20) OOT?DENGISEDESEHT?ERA?NETSIL. (21)
    is too “good” to be a real example, and is instead a “didactic example”, because it goes from 2 hits to 7 in one generation

    This neatly side-steps the fact that M & D explicitly introduced the example as a didactic one,as already cited at : E Partitioned Search Partitioned search [12] is a “divide and conquer” procedure best introduced by example. Consider the L =28 character phrase . . .

    And, it is not that it is “too good” an example that the case goes forward five letters in one gen, but that multiple go-corrects are rare in the config space, so it is unlikely that the didactic example would be a real world run; especially when we know as well that EIL sponsors a clutch of Weasel algorithms, none of which will typically behave like that.

    This is an agenda-serving failure to read reasonably and charitably in light of relevant context. (I would not want to be under inquisition at the hands of such men, nor should you, dear onlooker. Such, plainly will twist anything you say or do or do not say to suit themselves. Do you see why it is therefore dangerous to cede real institutional power to such?)

    3] 305: Unfortunately for kf, the first two generations in TBW are:WDL*MNLT*DTJBKWIRZREZLMQCO*P WDLTMNLT*DTJBSWIRZREZLMQCO*P Which only changes in two places, out of 25 incorrect letters.

    The run in question is:

    >> 1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL>>

    In the initial phrase, 1, three letters are already correct: N, *, T. in the next one just one letter goes correct in addition, S, as highlighted. The first asterisk also goes to an M. So, we see a double letter change, one going correct – which explains the advance towards target.

    To get his “unfortunately,” DNA-J imposes the idea that M & D have an algorithm working in which all incorrect letters vary but all but two them happen to pick the original state out of the 27 available. But this is a case of assuming that there is an algorithm in which all such letters change in every generation, and putting it in my mouth (not to mention those of M & D). My argument, however, was precisely that there is no such algorithm at work on M & D’s part, but an explicitly illustrative example of what partitioning is. [Cf 1 and 2 above.]

    In short this is a strawman game at work.

    It is easy to set up a strawman to look silly, but that has nothing to do with the reality of what is being pointed out. In this case, an illustration of the EFFECT of partitioning: In partitioned search, our search for these letters [once they have gone correct] is finished. , as M & D said, and as I cited above and highlighted.

    Note again: M & D do sponsor the publication of Weasel Algorithms, which can be genuinely deemed M & D Weasel Algorithms. NONE OF THE ALGORITHMS THEY SPONSOR SHOW THE PATTERN OF BEHAVIOUR THAT IS BEING STRAWMANNISHLY CARICATURED TO MAKE ME LOOK SILLY AND TO MAKE THEM SOUND DISHONEST. NONE: NADA, ZIP, ZILCH.

    It is fair comment to note, therefore, that M & D , when they do make Weasel type algors [through Atom acting as their agent], do not make anything that looks like the caricature being set up and knocked over.

    And, since this has been repeatedly pointed out but ignored in the rush to gleefully pummel a strawman, to insist on the strawman in the teeth of such a reasonable alternative is less than fair-minded and I daresay, less than honest.

    But then, ever since the days of Alcibiades [cf. my link to the other thread this morning], for evolutionary materialists the inescapable is-ought gap and cosequent inherent amorality and relativism of such avant garde atheism have always meant that in the end, might makes right.

    And we onlookers should take due note of how that leads such men to behave when they are in a position to owe duties of care but heeding the voice of duty runs counter to the agenda.

    Then, we should think twice about ceding further institutional or general policy making power to such men.

    4] 305, KF accuses me of “trying to drive a rhetorical wedge between latching and ratcheting”. I call him on this, saying . . . . To prove his point (that I drive a rhetorical wedge between ‘latching’ and ‘ratcheting’) he quotes my post highlighting his logical fallacy, which does not even contain the word ‘ratcheting’ : . . .

    Contrary to how the matter is presented in 305, a glance up at 302, point 5 will show:

    I am being accused of making false accusations. However, a scrollup will show that a primary reference is e.g. DNA-J, 285:

    Oh dear.
    We can agree that partitioned search, as accurately described by D&M in eqn22, latches.
    Unfortunately, you are using this fact to conclude that a (hypothetical) latching search is a partitioned search.
    All partitioned searches latch.
    Kf’s imagined Weasel latches.
    Therefore kf’s imagined Weasel is a partitioned search

    But, instead of this strawman and red herring muddles on undistributed middles etc, the defining characteristic of partitioning of search as just highlighted, as used by Marks and Dembski, is that correct letters are latched and ratcheting progress builds on what is achieved by making successive additions of correct letters through searching, until the whole target is cumulatively achieved. And, I am taking “partitioning” in the light of that usage, whatever other uses there may be in other contexts . . .

    In short, I first highlighted that the strawmannish syllogism DNA-J set up was about the undistributed middle. Then, I showed that “latching” and “ratcheting” spoke to the fact that PARTITIONED SEARCH, as used by M & D, is about the locking in of successful letters in generational champions, and the cumulative progress to target as more and more letters become latched.

    Thus, we see the evident ratcheting and latching effects in Weasel showcased run excerpts, c. 1986. (I then went on to discuss how the M & D analysis of the performances of such partitioned search was PREMISEED on the latching of successful letters.)
    The suppression of context therefore twisted my words into yet another silly strawman, which was duly pummelled. And the non-mention of “ratcheting” in the specific excerpt was just a distractive red herring.

    For, I SHOWED that ratcheting and latching are simply two sides of the same coin.

    To see why that is so, let’s re-examine the strawman, given that latching and ratcheting are two views of the same process:

    All partitioned searches latch. [True, by definition]

    Kf’s imagined Weasel latches. [Weasel c. 1986 credibly latches.]

    [Latching and ratcheting are two sides of the same process, whereby successful letters in a search will be retained in further generations of champions until the target is hit. This, being by M & D's definition for this context, partitioned search.]

    Therefore kf’s imagined Weasel [a weasel that latches] is a partitioned search

    See the difference? (And, see how the strawman was laced with loaded word ad hominems, too; with what rhetorical effect?)

    [ . . . ]

  309. 5] 305, All at once begging the question, and (brilliantly) re-defining the word “partitioning” (which has a specific mathematical meaning in D&M’s paper) to mean something entirely different. And thus, since HE thinks latching and partitioning are synonymns, any attempt to argue that there is a difference between them, or between mechanism and behavior, is “driving a rhetorical wedge between latching and ratcheting”, apparently.

    Of course, I have already shown how M & D defined partitioning, in terms of once a letter becomes on-target, the search for that letter is over. That is, it is locked in. progress to date is preserved, and further progress comes as new letters are guessed, resulting in ratcheting progress and cumulative selection to the target.

    But, the unwary, overly trusting reader might not check up to see that this is the case.

    6] 305, you invent totally novel meanings for words in order to avoid admitting defeat. ‘Mechanism’, ‘partitioning’, and the strictly telic use of ‘cumulative’.

    Outright, brazen falsehood.

    First, on two of the terms, I have simply cited the AmH Dict, a well known generally used, respected dictionary, and on the third I have demonstrably used the sense of the authors in question:

    CUMULATIVE: 1. Increasing or enlarging by successive addition. (In context, note how the showcased runs used by Dawkins c 1986 NEVER show a correct letter reverting. If you say cumulative in a context of such successive increases in proximity without exception, that makes the meaning clear but to those determined to wriggle out of the implications.)

    MECHANISM: 3. An instrument or a process, physical or mental, by which something is done or comes into being: (Here, I am the original person to speak. This is the sense in which I spoke of mechanism, a sense tat would be familiar to any Physicist, chemist or engineer.)

    PARTITIONING: Am H D. 2. To divide or separate by means of a partition. M 7 D, p. 1055: “In partitioned search, our search for these letters [once they have gone correct] is finished. ” (this one I did not use a dictionary on, but Marks and Dembski’s terms. THEY are the ones using the word in their context, and we need to identify THEIR sense. And the dictionary meaning makes their use seem very reasonable.)

    And, onlookers, it is clear that I have sought instead to correctly understand and address the situation, so the demonising ad hominems are utterly uncivil and unwarranted.
    DNA-J, you owe me an apology and retraction.

    7] 305, Citation with approval from BillB: Partitioning means to divide up the search into separate, independent units. WEASEL is not an algorithm that searches for individual letters, it is not partitioned.

    First, the facts to be explained are the sampled and showcased runs of generational champions, c. 1986:

     1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL
     1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL

    These runs show that in over 200 cases where letters go correct, they never once revert in the samples, in a context where it is common for incorrect letters to remain incorrect form decades of generations. So, it is credible – especially given the enthusiastic words in BW on “cumulative selection” [remember we have two multiplying lines of evidence here]– to see that the showcased runs did not have any reversions.

    We have been able to replicate such an effect of ratcheting-latching progress to target by generational champions by two algorithmic mechanisms: explicit latching and implicit latching, as has been demonstrated. These two mechanisms have the same effect on the relevant generational champions, and they will see the same pattern of accelerated progress to target relative to baseline random walk search.
    So, on explaining what was to be explained [ratcheted progress of generational champions], the two are plainly valid.

    Further to this, the D & M analysis as presented – and as already discussed by the undersigned — pivots on the latched effect; which as we note applies to generational champions.

    Therefore also, the internal processing difference between the two classes of mechanism [explicit latching mechanisms protect all mutants from varying successful letters, implicitly latched cases do not] – which is what is being pounced on and highlighted – is an irrelevancy to what was to be explained.

    But, a very convenient one for those determined – regardless of costs to truth, reasonableness and civility — to portray a mythical Dembski algorithm that diverges from the Dawkins algorithm sufficiently that Dembski can be impugned as making misrepresentations.
    But — as the very un-awarded status of the prize for this thread testifies — to begin with there is no known THE Dawkins Weasel algorithm c 1986. Just, reasonable reconstructions, and they can come in varieties that latch letters explicitly or implicitly. AND THE EIL SPONSORED BY DEMBSKI AND MARKS OFFERS A CLUSTER OF SUCH ALGORTIHMS THAT COVERS THE BASES.

    8] Dieb, 207: Isn’t that like gluing moths to trees – for tutorial reasons?

    Turnabout insinuation that tends to create an unwarranted perception of immoral equivalency.

    BACKDROP: One of the misleading icons of evolution was that he pepper moths presented from the 1950′s as illustrating how moths rested on tree trunks and it was contrasting colour that explained population shifts due to differential predation, as pollution darkened the trunks. Turns out moths don’t usually rest on trunks and the pictures were based on moths glued t three trunks where they did not usually rest.

    By contrast, Dembski and Marks on p. 1055 of the IEEE paper simply say that they are illustrating what partitioning is about, emphasising that the point is that when letters go correct [in context, for generational champions], they remain that way in future champions till the target is hit. This holds for explicitly latched and implicitly latched Weasel algorithm mechanisms. Their analysis – as was previously shown in 302 — is premised on the fact of latching, not the mechanism at work underneath.

    When the EIL sponsored by these men does present definite Weasel algorithms [with the source code available through a zip], it presents a cluster that covers the bases.
    So, there is no good reason to infer to misrepresentation of reality on M & D’s part. (by contrast, when he presented Weasel in BW, Dawkins had to admit that it was misleading in important ways ,” which I have discussed already.]
    _____________

    The pattern of distraction, distortion, demonisation and dismissal by darwinist advocates, sadly, plainly continues.

    That speaks volumes on the implications and impact of the amorality that is inextricably intertwined with the institutionally predominant evolutionary materialism that ever so plainly dominates Darwinland [formerly known as Christendom].

    GEM of TKI

  310. –kf,

    The ten sequences selected of course are in part a run of a Weasel type program with reversions.

    No, they are not. Especially not the tenth. I’m afraid you misunderstood my post. As is said in 288:

    Dembski and Marks start in their paper with the phrase:
    SCITAMROFN*IYRANOITULOVE*SAM
    I calculated a next generation using Dawkins’s algorithms with populations of 10,50 and 100 – and mutation rates of .04, .05 and .1. The tenth string in the list is the second generation given in the paper of Mark and Dembski.

    So, it’s not about latching, quasi-latching, or whatever. It’s just a comparison of the best strings of a second generation. And to spell it out: The string Dembski’s and Marks’s algorithm produces as a second generation is quite different in design from strings which nine runs of Dawkins’s program produce with various parameters as the best string of the second generation.
    This difference in design shows that the algorithms are different in design…

  311. kairosfocus is very eloquent, but he continues to get everything wrong.

    It seems I will only be able to get Dieb off this irrelvancy by being more detailed.

    The ten sequences selected of course are in part a run of a Weasel type program with reversions.

    Err. No they are not. Dieb’s post 115 describes how he ran 9 Weasels that cover the range of typical input values for the parameters Generation Size and Mutation Rate,to see how many letters would change in the first generational champion for a Weasel. The tenth row is the result for a partitioned search, as accurately described in D&M.
    DiEb’s point: you cannot get a Weasel search to look like a partitioned search. And, as I pointed out mathematically in post 305, you cannot get a partitioned search to look like the TBW example without millions of computer.years.

    I note that kairos “it’s just a flesh wound” focus has failed to provide any substantive response to any of the points raised in post 305. If any of the onlookers doubt this, I will happily clarify for them. But there is little point in arguing with someone who, when a logical fallacy in their argument is pointed out to them, responds with the same fallacious argument…

    From post 285:

    Oh dear.
    We can agree that partitioned search, as accurately described by D&M in eqn22, latches.
    Unfortunately, you are using this fact to conclude that a (hypothetical) latching search is a partitioned search.

    All partitioned searches latch.
    Kf’s imagined Weasel latches.
    Therefore kf’s imagined Weasel is a partitioned search

    All ostriches have two legs
    Kf has two legs
    Therefore Kf is an ostrich.

    It is a famous logical fallacy. Surely you can see this. You cannot (e.g. 308) use it to try to prove anything kf.

  312. Onlookers:

    We first and foremost observe above no compunction over abusive, manipulative and disrespectful rhetoric and many misleading arguments, even in the face of step by step corrections. Just, rushing on to he next objections as though nothing more serious than a debate game were at stake, or vanishing behind the cloud of poisonous smoke from burning, ad hominem soaked strawmen.

    We should therefore take the prudence to act in light of the clear observation of High Machiavellian tendencies at work. (And, we should note how the widespread acceptance as “science” of the amoral philosophy of evolutionary materialism naturally promotes such tendencies, as was discussed yesterday in the other thread.)

    Now, let us focus a few moments on several further rhetorical gambits:

    1] Dieb, 310: I calculated a next generation using Dawkins’s algorithms with populations of 10,50 and 100 – and mutation rates of .04, .05 and .1.

    This of course would give rhe appearance of a sequence of generational champions that has high reversions, so no latching or quasi-latching behaviour.

    The argument is an insincere strawman intended to create a “gotcha.”

    Sad.

    2] 310, The string Dembski’s and Marks’s algorithm produces as a second generation is quite different in design from strings which nine runs of Dawkins’s program produce with various parameters as the best string of the second generation.

    Of course, irt was already correctivley pointed out that there is no one “Dembski’s and Marks’s algorithm”, as the GUI hosted at EIL shows: several algorithms, taking a diversity of apporaches to Weasel. Instead, despite this being already corrected, we have a strawman mischaracterisation of the didactic example to illustrate what partitioning of a search means. (Observe onlookers, Dieb NEVER engages the import of the cluster of Weasels sponsored by EIL, which would at once show that there is no reasonable reading of p. 1055 of the IEEE paper that would support the conclusions being advanced through a patent – and now plainly willful — misrepresentation.)

    And, when the silly strawman algorithm is applied to the string used by Dawkins, then it will produce the intended silly results. A cheap gotcha but not an honest one.

    Inexcusable.

    And, ever so sad.

    3] DNA-J, 311: DiEb’s point: you cannot get a Weasel search to look like a partitioned search.

    This, too relies on the silly strawman algorithm manufactured out of a didactic example intended to illustrate what partitioning does. Namely: once a letter goes correct in a given generational champion, it remains that way all the way tot he target – as Weasel o/ps showcased in 1986 credibly show.

    And, Weasels with the implicit latching and ratcheting to the target as described by Dembski and Marks are long since DEMONSTRATED, on EIL’s Weasel ware.

    It seems I need to reproduce, e.g. Run B from April 9, 2009 – the day when the issue was definitively settled by demonstration of latching, quasi-latching, and non-latching behaviour using the EIL “proximity reward” search algor (one of their stable of weasel type algors):

    ____________

    RUN B, 500 pop/gen, 4% per letter mut rate:
    1. MEL LSI YHXMAJLMDGMVKTSKGW
    2. MEL LSI YHXIAJLMDNMVKTSKGW
    3. MEL LSI YHXISJLMDNMJKTSKGW
    4. MEL LSI YHXISJLMDN JKTSKGW
    5. MEL LNI YHXISJLDDN JKTSKGW
    6. MEL LNI YHXISJLDDN JKTEKGW
    7. MEL LNB BHXISJLDDN JKTEKGE
    8. MEL LNB BHXISJLIDN JKTEKGE
    9. MEL LNB BHXISJLIDN JKTEKSE
    10. MEL LNB BHXISJLIDN JKTEKSEL
    11. MEL LNK BHXISJLIDN JKTEKSEL
    12. MEL LNK BHXIS LIDN JKTEKSEL
    13. MET LNKV BHXIS LIDN JKTEKSEL
    14. MET LNKV BHXIS LIDN AKTEKSEL
    15. MET LNKV BHXIS LIDE AKFEKSEL
    16. MET LNKV BHXIS LIKE AKFEKSEL
    17. MET LNKS BHXIS LIKE AKFEKSEL
    18. MET LNKS BH IS LIKE AKFEKSEL
    19. MET LNKS BH IS LIKE AKFEKSEL
    20. MET LNKS BH IS LIKE AKWEKSEL
    21. MET INKS BH IS LIKE AKWEKSEL
    22. MET INKS BH IS LIKE AKWEKSEL
    23. MET INKS BH IS LIKE AKWEKSEL
    24. MET INKS IH IS LIKE AKWEKSEL
    25. MET INKS IH IS LIKE A WEKSEL
    26. MET INKS IH IS LIKE A WEASEL
    27. MET INKS IH IS LIKE A WEASEL
    28. METHINKS IH IS LIKE A WEASEL
    29. METHINKS IH IS LIKE A WEASEL
    30. METHINKS IH IS LIKE A WEASEL
    31. METHINKS IT IS LIKE A WEASEL
    ______________

    This is a case of implicit latching or at least quasi-latching. (As I recall, the correct letters went red, and no red letter reverted to black.)

    You will see that the 31-gen run of generation champions to the weasel target is actually a little better than the 43 gen one published by Dawkins in 1986 in BW, probably due to the population size. (4% odds of mutation per letter would give about 1 letter mutated per member of a generation on average.)

    This – contrary to DNA-J’s confident declarations — is an implicitly latched, ratcheting, cumulatively selected, progressive run of generational proximity champions to target. And, it looks rather like the two runs published by Dawkins in 1986, except that this is not every tenth generation shown, but every generation shown.

    QED.

    Since April 9th, and linked directly from point 15 my App 7, the always linked. (That is, the claims I am correcting were made in the context of refusing to first check easily accessible facts.)

    4] Repeating a fallacy:

    I will slightly update my correction of DNA-J’s fallacy, as I have given a concrete example — run B of April 9 — from an undeniable Marks and Dembski- approved, EIL-sponsored algorithm:

    All partitioned searches latch. [true by definition]

    Kf’s imagined Weasel [Run B above, based on EIL's real world Weasel program] latches [implicitly].

    [SUPPRESSED, MATERIAL CONTEXT: Latching and ratcheting, in the context of Weasel algorithms with the relevant behaviour similar to that credibly observed in the showcased examples by Dawkins c 1986, are two aspects of the same process. "Latching" focusses on how in generational champions, once letters go correct under certain circumstances, they remain that way in future generations all the way to target. "Ratcheting," on how such locked in successful letters then provide the baseline for progress as futher letters are discovered and similarly locked in as the search homes in on the target through hotter-colder proximity signals. The search is therefore partitioned so that successful letters in generational champions to date are preserved from loss of correct state. This can be done explicitly or implicitly, as Run B demonstrates. In either case, the result is cumulative progress to target – i.e. By successive addition of successful letters. And, once we observe the latching effect, the mathematical analysis presented in the M & D IEEE paper, p. 1055 applies, as was already discussed by the undersigned, above. Thus, ratcheting and latching cannot be dynamically separated in the context of such a weasel run. And, Run B above is an illustration of this in action.]

    Therefore kf’s imagined Weasel [Run B above, an implicitly latched, ratcheting, cumulatively progressive, partitioned and selected search, based on the Marks and Dembski EIL "proximity reward search" algorithm] is a partitioned search [by virtue of the dynamics or mechanism of a latched, ratcheted search]

    In short, the attempt to force-fit case B etc into the imagined fallacy of the undistributed middle term [forgive my error of memory on this . . . it's been a long time since I thought in terms of syllogistic terminology – I usually just draw the relevant Venn diagram and directly see the set relationships instead of bothering with the complexities of classical syllogistic arguments] is based on a misunderstanding of the observable dynamical relationship between latching, ratcheting and cumulative selection in weasel type algorithms.

    In short, one cannot properly separate latched searches from partitioned searches, as ratcheting behaviour and associated cumulative progress to target are the dynamical bridge that inherently and inseparably joins the two.

    That is, the set of partitioned searches is here EQUIVALENT to the set of latched, ratcheting searches: it is necessary and sufficient for a search to be partitioned in the sense used by Marks and Dembski on p. 1055 of their IEEE paper, that it be (latched and ratcheting).
    ____________

    GEM of TKI

  313. PS: Onlookers, note that the ratcheting and latching o/p behaviour to be explained is that for generational champions as Weasel 1986 showcased. This can be achieved explicitly by using say a mask register to lock up successful letters from further change. It may also be achieved implicitly through a mechanism that uses a population size big enough and a per letter mutation rate small enough such that by overwhelming probability, each generation seeded from a previous champion or the original string will have in it unchanged members [and/or those with a letter changed from one incorrect form to another that does not affect already correct letters.] In such a generation, with a relatively small size such that double etc letter mutations are rare enough not to show up among generation champions in a significant fraction of runs, no increase in proximity and single step increases will dominate behaviour. Under these conditions it will not be hard to find runs that show cumulative progress to target without reversions of successful letters of generational champions. Such runs are implicitly latched, and show ratcheting without slips (NB: as the “dog” wears in say a baitcaster reel, the anti-reverse action can show occasional slips). Run B above is a case in point of such implicit latching. (Beware of the rhetorical tactic of objectors who will try to slip in the definition that latching can only mean explicit latching.)

  314. PPS: All A’s are B’s is a set relationship. Some A’s are B’s is a set relationship with existential import — at least one member of A, a exists, and is also a member of B, another set. No A’s are B’s is a statement about non-overlap of sets, and some A’s are not B’s is a statement that at least one member of A, a exists, and is not in set B as well. (And I am leaving off for the moment the issue of the empty set, the division between classical and modern logic.)

    The undistributed middle term is a case where relevant overlap fails.

    In the case of run B, it is an existing example of an implicitly latched, ratcheting, partitioned search. And, there is a dynamical connexion such that latched searches will be partitioned. So, if a is a member of A then it will be partitioned search due to a mechanism that causes ratcheting behaviour.

    So, in terms of the sets at work:

    All partitioned searches latch:

    –> partitioned seqarches, P are a subset of latched searches, L

    –> but, suppressed context: due to the involved dynamics, we can also see that Latched searches L, are a subset of partitioned searches P

    –> That is, the two sets are equivalent, due to the dynamics of ratceting

    Kf’s imagined Weasel [Run B] latches.

    –> there exists b, such that it is a member of L

    –> but also we know though the dynamics of ratcheting, that members of L are also members of P, the two sets being equivalent.

    Therefore kf’s imagined Weasel [run B] is a partitioned search

    –> As, we have reason to see why members of L will be members of P.

    –> In short the imagined fallacy is begging the question of the relationship between sets L and P. And, we have reason to see that L is not a proper subset of P but an equivalent set to P.

    –> And, see how thinking in terms of sets untangles the complexities of syllogistic reasoning? [Thank you, Irving Copi!]

  315. –kf

    This of course would give rhe appearance of a sequence of generational champions that has high reversions, so no latching or quasi-latching behaviour.

    The argument is an insincere strawman intended to create a “gotcha.”

    You lost me. I introduced the ten strings in 115, fully explaining them as

    I took the string
    SCITAMROFN*IYRANOITULOVE*SAM
    and calculated a next generation using Dawkins’s algorithms with populations of 10,50 and 100 – and mutation rates of .04, .05 and .1. The tenth string in the list is the second generation given in the paper of Mark and Dembski.

    and I asked:

    Can anyone spot a difference in the design of the strings? Anyone? KF? Anyone?
    I repeated this question in 263, 288, and, in a shorter form in 291 and 297 until you came up with your reply.
    I don’t think that I was misleading any attentive reader.

  316. Dieb:

    It is fair comment that you know the relevant context.

    G’day.

    GEM of TKI

  317. -kf,

    This, too relies on the silly strawman algorithm manufactured out of a didactic example intended to illustrate what partitioning does. Namely: once a letter goes correct in a given generational champion, it remains that way all the way tot he target – as Weasel o/ps showcased in 1986 credibly show.

    Dembski and Marks describe the algorithm they use to get their didactic example fairly well, I think. But I don’t even have to know their algorithm (and therefore, don’t have to come up with a strawman algorithm), as they give me their first and second generation in their paper. And this second generation looks quite different to a second generation derived by Dawkins’s algorithm, implying that there is a difference in the design of the algorithms used.
    For me, that’s the relevant context.

  318. –kf
    another thought: on the Evolutionary Informatics Labs website, the evaluation of the fitness function is compared with questioning an oracle: you give a string to the oracle, and it gives you an answer for its fitness. Most implementations I’ve seen use as the fitness of a string in a weasel algorithm the number of correct letters, i.e., a number between 0 and 28.
    That is, taking the string SCITAMROFN*IYRANOITULOVE*SAM to the oracle, it would answer 2.
    Now, look at the description of the algorithm in the paper of Dembski and Marks. Could you give me the answer of the oracle for their fitness function for the string above? Is it 2, too? Another number? Something else?

  319. Onlookers:

    I have been busy surrounding an election cycle here.

    I note that Dieb just above somehow manages to ask about oracles while missing the elephant in the middle of the room: there is plainly no one Marks-Dembski algorithm for Weasel type programmes, but several approaches.

    A common factor for most of these is that oracles broadcast warmer-colder signals to successive generations of guesses, until they hit the target. that is, warmer-colder signals are a feature of targetted searches.

    And, of course, the didactic example given to illustrate the effect of latching in a ratcheting search (a physical ratchet “dogs” progress to date using a spring-loaded pawl mechanism that served as a check that prevents reversal: one way progress . . . ), is not any THE M-D algorithm, and to set it up as though it is THE opposite to a THE Dawkins algorithm (that here is any one THE Dawkins algorithm is an open quesiton, strictly speaking – the focus for the prize offer) is a strawman fallacy.

    GEM of TKI

  320. PS: I of course refuse to go off on his latest red herring headed off to as strawman soaked in ad hominems. Dieb knows that there are many possible distance to target metrics usable in Weasel type programs as a component of the closest-to-date filter.

  321. –kf
    at least, there is the Dembski-Marks algorithm as described in their paper, and there is the Dawkins algorithm as described in his book.

    But the real problem with your answer:

    A common factor for most of these is that oracles broadcast warmer-colder signals to successive generations of guesses, until they hit the target. that is, warmer-colder signals are a feature of targetted searches.

    Oracles not necessarily broadcast warmer-colder signals. To quote David H. Wolpert and William G. Macready in their paper No Free Lunch Theorems for Optimization:

    It is common in the optimization community to adopt an oracle-based view of computation.

    But as you spoke about warmer-colder signals:The algorithm described by Marks and Dembski in their paper and claimed by Dembski here at Uncommon Descent to be Dawkins’s algorithm of The Blind Watchmaker doesn’t work with warmer-colder signals, while the algorithm in the description of Dawkins’s book would….

    The answer of the oracle in the D&M case is the position of the correct letters, which can be represented by L bits.

    The fitness of a string OTOH can be represented by the Hamming distance (Dembski and Marks, p. 1056), a number between 0 and L, i.e., ~ log(L) bits…

  322. I of course refuse to go off on his latest red herring headed off to as strawman soaked in ad hominems.

    If you post your mailing address, I would be quite happy to send you a thesaurus.

  323. Onlookers:

    The above dismissive and misdirecting arguments inadvertently underscore just how far this thread has brought to light the distractive, distorting, demonising [or at best belittling] and dismissive tactics used by ever so many Darwinist debaters here at UD.

    1] Dieb, 321: there is the Dembski-Marks algorithm as described in their paper, and there is the Dawkins algorithm as described in his book.

    Dembski and Marks — as has long since been shown, but is being brazenly brushed aside to push an agenda of talking points — do not describe a realistic algorithm; and on their web site EIL gives a relevant context that shows they are aware that Weasel algorithms producing results and meeting the Dawkins description a la 1986 come in many flavours.

    The EXPLICIT purpose of the illustrative example they provide o p. 1055 of the EIL paper is to show the effect of partitioning: latching of successful letters — i.e. prevention of slip-backs by a mechanism in the program [which can be either explicit or implicit]. And their mathematical analysis pivots off such latching. (And in the case of G generations of size S, the number of queries to date, Q, is best understood as Q = G*S.)

    All of this has long since been shown.

    Just, willfully ignored and snowed under by wave after wave of demonstrably false and at minimum irresponsible declarations to the contrary. (But, repetition of such Darwinist false declarations does not transform such into truth. And this is all too redolent of the string of falsehoods and willfully untruthful — neglect of the duties of care of truthfulness and fairness is sufficient to make the falsehoods willful and slanderous — misrepresentations directed at the Intelligent Design movement in general, and even the old Creationists! [Cf the Weak Argument Correctives above].)

    Similarly, one root of the exchanges over the past several months is that Dawkins’ language and showcased examples of 1986 are NOT sufficient to establish the algorithm in use c 1986.

    Indeed, that is the very reason why this contest thread asks for credible code.

    As to the onward claim — notice the telling absence of a specific link, citation or reference [a warning sign that something is being twisted out of context or worse . . . ] — that Dembski “confesses,” in fact the demonstrable and DEMONSTRATED (cf 302 above) point of the M & D analysis in the IEEE paper p. 1055, is that once an algorithm shows latching effects in the runs of generational champions — which DEMONSTRABLY can be achieved explicitly or implicitly [and Dawkins' remarks c 1986 are insufficient to determine which of these applies; it is on later remarks that implicit latching is to be preferred as best explanation] — then the following math applies.

    As was shown by me at 302 above; days ago now.

    2] Oracles not necessarily broadcast warmer-colder signals.

    Whoever said that oracles — i.e. in general — only broadcast warmer-colder signals?

    Certainly, not he undersigned. (In other words words are here being twisted to make up a strawman to pummel.)

    I spoke to THESE cases, in the specific context of Weasel c 1986. And in that context, here are Mr Dawkins’ words in BW, as are cited several times above and in other recent threads, as well as being instantly accessible in App 7, the always linked:

    It [Weasel c 1986] . . . begins by choosing a random sequence of 28 letters … it duplicates it repeatedly, but with a certain chance of random error – ‘mutation’ – in the copying. The computer examines the mutant nonsense phrases, the ‘progeny’ of the original phrase, and chooses the one which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL . . . . What matters is the difference between the time taken by cumulative selection, and the time which the same computer, working flat out at the same rate, would take to reach the target phrase if it were forced to use the other procedure of single-step selection: about a million million million million million years. This is more than a million million million times as long as the universe has so far existed . . . .

    Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target . . .

    The warmer-colder proximity to target metric that rewards “mutant nonsense phrases” — the very opposite of survival of the fittest [thus functional] — could not be clearer.

    3] The algorithm described by Marks and Dembski in their paper and claimed by Dembski here at Uncommon Descent to be Dawkins’s algorithm of The Blind Watchmaker doesn’t work with warmer-colder signals

    This is of course mere drumbeat repetition of a demonstrably false statement, to create the impression that it is the truth.

    Again, until you and your ilk cogently address the FACT that M & D in their EIL site sponsor a cluster of Weasel algorithms, for the explicit purpose of showing how the various interpretations thereof work, and the gaps between such and the credible need of complex function to emerge first before it can be improved on differential success, this is a deceptive agit-prop tactic.

    And, whatever algorithms are consistent with the Dawkisn description just cited, plainly work off — non-functional — increments in proximity to target, i.e. a case of warmer-colder signals.

    4] The fitness of a string OTOH can be represented by the Hamming distance . . .

    And of course this plays off an ambiguity in the term “fitness.”

    I repeat, Weasel c 1986 works off active information injected through targetting and rewarding mere — and explicitly acknowledged as non-functional — proximity. No amount of rhetoric to the contrary can change the force of that acknowledged fact.

    5] LH, 322: I would be quite happy to send you a thesaurus.

    This, in response to my underscoring that I have again seen the abusive rhetorical tactic of distractions [red herrings] led away to distortions [strawmen] and used to demonise and/or belittle [soaked in ad hominems and ignited], thence confusing, clouding, poisoning and polarising the atmosphere in which discussions would have to take place.

    LH, sadly, has now added his own contribution to today’s increment another case of the same tactics.

    _____________

    We would do well to learn the pattern, and learn its — historically warranted (says the ghost of Socrates) — consequences if it is allowed to grow unchecked: destruction of civility, enabling and leading to the rise of oppression, spreading injustice and tyranny.

    In particular, we should note the habitual, willful insistence — in the teeth of easily accessible corrective information — on half truths, misrepresentations and outright falsehoods in service to ad hominem attacks and snide dismissals, on the part of darwinists.

    If such cannot be counrted on to have regard for basic directly accessible facts and respect for persons on a relatively level playinfg fields, they can have no credibility on matters of the reote past tha tiws unobserfgvable. And, they plainly cnnot be trusted to be fair-minded or just.

    that’s a sad bottomline to have to draw. but it is unfortunately well-warranted by evidence.

    Now, the issue is whether, being forewarned, we will be forearmed and determined to stop the rising tide of darwinist incivility before it is too late.

    Onlookers, after this, we need to simply look sot see if there are signs of compunctions on the part of Darwinists, and of recognition of corrections leading to amending of ways.

    Absent such, this thread will have achieved something else, which is perhaps even more important if we care about science and our civlisation: it demonstrates the utter willful untruthfulness and unfairness of typical darwinist approaches to origins science issues and to those who challenge the holy rulings of the a priori materialism neo-magisterium wearing the holy vestments of scientists’ lab coats.

    G’day.

    GEM of TKI

  324. KF, this is what happens to people after four years of liberal arts.

    Get out the torches and pitchforks! We have a lot of hay to burn!

  325. And, whatever algorithms are consistent with the Dawkisn description just cited, plainly work off — non-functional — increments in proximity to target, i.e. a case of warmer-colder signals.

    Here, we agree, I think: Algorithms consistent with Dawkins’s description do work with warmer-colder signals.

    The algorithm described by Marks and Dembski (or stated as an tutorial example, or whatever) does not.

  326. BTW, if you take Q=G*S, you assume that within each generation, the correct letters are latched. But this isn’t true, as there is no (to borrow your terminology) explicit latching.

  327. I downloaded Weasel from
    http://home.earthlink.net/~matthewjheaney/

    and as far as I could see, it was not latching. Furthermore, as far as I can see, the purpose of Weasel is just to demonstrate the effect of selection on fitness. For evolution to be true; selection for fitness must be present. Fit or perish; in IBM lingo Think or Thwim.

    I don’t know if a comment that I found at PT is relevant with respect to this debate, but I found it interesting:

    In the case of numerical simulations of hydrodynamics, for example, the simulations use the laws of physics, like the Navier-Stokes equations which govern the flow of fluids. That is all. If we knew what we going to get, we wouldn’t bother with such simulations. We do these simulations because in most cases the problems under study are not possible to do experimentally or too costly. Numerical simulations of fluid flow have practically eliminated the need for wind tunnel testing in aircraft design. Why? because they are accurate representations of what nature does.

  328. Cabal:

    I believe KF would respond by claiming that studying fluid dynamics is a strawman soaked with oil of ad hominem attacks that distract from the issue of the origin of fluids, that the fluids in simulation only behave that way because they have been intelligently designed to do so, and if you disagree with him about any of this then you are spreading half truths, misrepresentations and outright falsehoods in service to ad hominem attacks and snide dismissals.

    KF:

    I notice you have devoted almost half of you last post to making personal attacks against scientists who study nature and commentators who disagree with your unorthodox interpretation of the facts. I will repeat Learned Hands offer to send you a thesaurus – I could send you a bible as well as there are some important life lessons in there about humility, tolerance and the concept of ‘turning the other cheek’.

    The people arguing with you here are not trying to distract, poison or dismiss, they are directly addressing the facts.

    And before you come back with a comment about turnabout accusations lets remember that you are always the one to cast the first stone – Perhaps you misunderstood that lesson in the bible?

  329. Where – and how – do you introduce µ (the mutation rate per letter) into eq. 22?

    Could you please calculate q(Q) for S = 500, µ=.05? Just some numerical values?

    Thanks!

  330. Cabal:

    Did you credibly download Weasel as composed by Mr Dawkins in BASIC or Pascal, c 1986, apparently on an Apple II?

    Failing that — and if you did so and have credible 1986 Dawkins code, you are the prize winner — then all we have to go on is the description and excerpted runs from that time. Which are capable of two main interpretations: implicit and explicit latching and ratcheting as the generational champions ran to target. (Cf my notes and excerpts here in APP 7 the always linked. It would have been helpful if you would have read this first before commenting adversely. [You will understand that your remarks, in the tone delivered and in the teeth of easily accessible corrective information, frankly, come across as unhelpful or worse. Please, do better next time.])

    Subsequently Mr Dawkins has indicated that the original code is not forthcoming, but that there are many legitimate replications on the web.

    EIL’s collection reproduces the range of legitimate interpretations of Weasel; and with source code available in a Zip.

    Under certain circumstances [big enough pop size low enough mut rate per letter for no-change and one-step changes to dominate, particular filter . . . cf the latched runs as demonstrated] , the “proximity reward” case will latch implicitly in at least some cases, and since Weasel 1986 is a matter of showcasing, that is good enough. Also, insofar as Mr Dawkins claims that his Weasel 1986 did not latch what has been called “generational champions” above and elsewhere EXPLICITLY, it seems implicit latching and associated ratcheting is the best explanation of his results as at that time. (In 1987, he showcased runs on BBC that appear to either be the individual members of the generational pops, or else a run sufficiently detuned that it does not latch.)

    In short, your between the lines insinuation above that the claim that certain interpretations of weasel can implicitly latch [cf demonstrations from here on, April 9th 2009 in earlier discussions at UD] is illegitimate is at best ill-informed.

    Now, too you go on to say something that is even more misleading:

    as far as I can see, the purpose of Weasel is just to demonstrate the effect of selection on fitness. For evolution to be true; selection for fitness must be present. Fit or perish; in IBM lingo Think or Thwim.

    There is a world of difference, Cabal, between artificial and targetted selection of non-functional “mutant nonsense phrases” on mere increment in proximity to target, and what natural selection is supposed to do: summarise the effect of superior functional fitness in an environment over time whereby the functionally fitter sub-population survives at the expense of the less fit.

    But the problem is that the threshold of function in question for life forms is complex and specific, based on an abundance of algorithmic information. That is, it comes in islands in large configuration spaces and you have to get to the shore before you can hill-climb by RV + NS.

    But to get to the shores of such an island within the accessible resources of the observed cosmos is then a major challenge as has ever so often been pointed out and justified in this blog.

    In short RV + NS might be able to account for some varieties of micro-evolution, but it cannot account credibly for he origin of body plans [10's - 100's of mega bits of functional info] or the first body plan [100's of k bits of functional info]. For, just 1 k bit of functional info stipulates a config space of 1.07 * 10^301 possibilities, where the number of states of the observed universe across its thermodynamically credible lifespan — ~ 50 mn times its age to date on the usual big bang timeline from 13.7 BYA — is less than 1 in 10^150 of this, i.e. not statistically different from zero.

    In short, Weasel, from 1986 on, created a misleading impression of a “solved” problem, while not actually addressing the real issue.

    And, unlike easily confirmed and validated computational fluid dynamics simulations, Weasel is not a good match to nature — which Dawkins himself admitted in the text of BW as I and others have excerpted and discussed — and it is trying to replicate a claimed process that being in the remote and ancestral past would be in-principle unobservable.

    In short PT as usual is misleading.

    And Cabal, you can do better than that, man.

    GEM of TKI

  331. Onlookers:

    BillB — who long since slipped over into the land of the uncivil — is simply playing at turnabout accusatory rhetoric.

    You will easily see that above in the posts he would impugn and in many others above thence the onward or always linked, I have addressed matters cogently on the merits, step by step, again and again, in painstaking details.

    Just, the details on the merits — and truth is “that which says of what is that it is and of what is not that it is not,” not the expulsion-enforced pseudo-consensus view of today’s neo-magisterium with their a priori Lewontinian materialism, whether openly metaphysical or implicitly so [aka methodological naturalism] — happen not to be convenient to BillB; who still has not apologised for twisting my corrective words on the rhetorical tactics he is again using into a blatantly false accusation of trying to push him into the same boat as presumably guilty rape accused.

    (BillB: If you insistently use the tactics of sleazy attorneys in courtrooms, who set out to discredit the victims to distract attention from the facts on the merits; that is bad enough for me.)

    G’day again.

    GEM of TKI

  332. KF:

    You have consistently failed to address matters cogently on the merits, step by step you have avoided the real issues, again and again, in painstaking irrelevance.

    If you want to engage in civil discourse then be my guest, it would make a welcome change from your constant distractions and ad hominems. Instead you seem to prefer to sling mud from the gutter. You insistently use the tactics of sleazy attorneys in courtrooms, who set out to discredit opponents and distract attention from the facts on the merits.

    You are not the victim, you are the perpetrator.

  333. Aha! I think I see your point, kf.
    Reading post 312, you use Atom’s Proximity Reward Search to showcase the latching behavior of Weasel. Run B of April 9th 2009 shows behavior just like the runs in TBW.
    In fact, you demonstrated this result with six runs of Atom’s Proximity Reward Search from EIL.
    And as you so rightly pointed out in April:

    More importantly, SO SOON AS IT WAS REPORTED THAT MR ELSBERRY HAS PASSED ON TESTIMONY THAT MR DAWKINS DID NOT EXPLICITLY LATCH WEASEL 1986, I AND OTHERS HAVE ACCEPTED THAT; AND WE HAVE INFERRED THAT WEASEL 1986?S O/P IS THEN BEST EXPLAINED ON IMPLICIT LATCHING. (The credibility of this explanation has been now abundantly and directly confirmed; thanks to Atom’s public spirited effort.)

    [Emphasis DNAJ's]

    So can we stipulate that TBW Weasel corresponds to Atom’s Proximity Reward Search at EIL? A simple ‘yes’ or ‘no’ will do.

    An answer that lacked the words latching, ratcheting, ad hominem, oil-soaked, red herring, and strawman would be nice, too.

  334. Onlookers:

    More distortions from BillB.

    And, even more sadly, blatant falsehoods declared confidently.

    GEM of TKI

  335. DNA-J:

    Your last is a refreshing contrast, especially given the just above.

    From April 9, the day it was announced, I have consistently used Atom’s Adjustable Weasel as a good example of the sort of Weasel algorithm that can show implicit latching, under certain conditions.

    Remember, as the Weasel 86 excerpted runs are showcased and demonstrate apparent latching in a context where from Elsberry et al, it is believed Dawkins did not explicitly latch, the question of implicit latching is relevant. It is demonstrably achievable in SOME cases. (NB: Some of the runs I put up on getting the new toy, are of quasi-latching and the like. Notice how I also showcased substitutions where we see reversion in which another letter advances to compensate. I also think I gave a case that ran on and on and on before finally hitting target with a lot of reversions etc. One run had a long lock on to substitutions on the last letter before finally hitting home.)

    The point is, that Weasels on proximity reward are capable of complex, widely varying behavour. Not even the probabilities of letters advancing in the generation champions are constant across a run, especially as it gets close to home!

    Of these many behaviours, some will show implicit lastching of genration champions, and if that is what looks like a good showcaser, you may weell put that in your book and magazine articles. (Milikan’s oil drop experiment lab notebook is a notorious case of showcasing in Physics by the way: “Beaut, Publish!” says he in the margin . . . onlooking historians and philosophers of science cringe. But, his results are what gave us our first “good” look at the charge of the electron.]

    I trust that helps.

    GEM of TKI

  336. That sounds like a “Yes”.

    So can we stipulate that TBW Weasel corresponds to Atom’s Proximity Reward Search at EIL?

    “Yes” or “No”?

  337. Just to note that if it wasn’t for the likes of me and the hundreds of thousands of colleauges throughout the world who are proud lab coat wearers, the planet would be in a very much worse way than it is now.

    kairosfocus’ anti-science rhetoric shows him in a very bad light indeed, as one of those who would indeed take society back to the Dark Ages if they had the opportunity.

  338. DNA_Jock:
    I have asked kf more or less the same question over 10 times now, for example in post 194 here.

    He will continue to avoid answering it. Maybe the reason is that it is so obvious that these two searches, called “Partitioned” and “Proximity Reward”, are completely different.

  339. FrogBox,

    Just to note that if it wasn’t for the likes of me and the hundreds of thousands of colleauges throughout the world who are proud lab coat wearers, the planet would be in a very much worse way than it is now.

    kairosfocus’ anti-science rhetoric shows him in a very bad light indeed, as one of those who would indeed take society back to the Dark Ages if they had the opportunity.

    Advancement is not limited to lab coat wearers, it is only limited to human ingenuity, and on this score kairosfocus can speak as well as anyone, indeed better than someone who wears a lab coat. Lab coats don’t come with the art of ingenuity built-in, and without folks like kairosfocus, lab coats would be a self aggrandizing group, with no accountability and no special training in actual broad thinking. Surely you’re not willing to say that labcoats gives a mind a special monopoly on ingenuity and rationality? If you are, that is called scientism, which is a philosophy, which other reasonable men can critique and which has no special place in the world of thinking men. Who would take us back to the Dark Ages are those who think that the only thing that matters is whatever folks who wear lab coats think, for they will impose whatever they want on the rest of humanity, which will be the opposite of the Enlightenment, and indeed, may be called the next age of Endarkenment.

    “Education without values, as useful as it is, seems rather to make man a more clever devil.”
    C.S. Lewis

  340. Advancement is not limited to lab coat wearers, it is only limited to human ingenuity, and on this score kairosfocus can speak as well as anyone, indeed better than someone who wears a lab coat.

    This kairosfocus seems to be an interesting fellow. I’ve followed his valiant fight here as a lurker for sometime, but haven’t run across him outside Uncommon Descent. I’d love to know more about what he does IRL.

    Thanks!

  341. This kairosfocus seems to be an interesting fellow. I’ve followed his valiant fight here as a lurker for sometime, but haven’t run across him outside Uncommon Descent. I’d love to know more about what he does IRL.

    He spends a lot of time pontificating about herrings, oil, straw, and men. Perhaps he manufactures fish oil, pressed from herrings by men wearing straw hats? Then again, judging from the length of his comments, he may sell bandwidth. I can’t imagine any other reason for using so much of it. Now that I think about it, if we go by the content of his posts, I’d say he’s cornered the market on vitriol. That’s a kind of fish oil, isn’t it?

  342. –kf

    due to moderation, #329 popped up in the middle of the thread. Could you answer to it?

    Thanks…

  343. Clive,

    When you said

    Advancement is not limited to lab coat wearers, it is only limited to human ingenuity, and on this score kairosfocus can speak as well as anyone, indeed better than someone who wears a lab coat.

    I am assuming you meant that there is at least one lab coat wearer who has advanced humanity less that kairosfocus. I think we can happily concede that point. For a moment there, however, I thought you meant that kairosfocus can speak to human ingenuity better than anyone who wears a lab coat.
    Nearly fell off my chair.

    Surely you’re not willing to say that labcoats gives a mind a special monopoly on ingenuity and rationality?

    A monopoly? That would be silly. There is however a rather impressive selection in favor of those traits, but that brings me perilously close to being on-topic, which would scarcely honor kairosfocus.

    without folks like kairosfocus, lab coats would be a self aggrandizing group, with no accountability and no special training in actual broad thinking.

    Now, I’ve met and worked with a lot of lab-coat guys, and I’ll admit that there are some pretty impressive egos amongst them, but, as a whole, I have yet to meet a less self-aggrandizing group. Philosophers, on the other hand, take the cake.

    I am a little puzzled as to which of kf’s contributions to humanity you are touting here. His contributions to Mechatronics seem rather lame to me – he has made much bigger name for himself in apologetics and evangelism, so this is what I am assuming you are referring to Clive.

    So here’s my offer to you Clive: I promise to forego the benefits and work product of people who teach evangelism, if you promise to forgo the benefits and work product of people who develop pharmaceutical products.

    Do we have a deal?

  344. “I promise to forego the benefits and work product of people who teach evangelism, if you promise to forgo the benefits and work product of people who develop pharmaceutical products.”

    DNA, Do you work for big pharma? You were talking about science and then mentioned big pharma. Doesn’t make sense.

  345. 345

    laughable,

    I tried Atom’s “Proximity Reward Search” for the phrase “ME THINKS IT IS LIKE A WEASEL” several times, and each time a correct letter was attained, that letter stayed latched. Not so for Dawkins’ video demonstration of the “weasel” program.

    So I don’t think it’s the same or a similar program. Am I wrong?

    However, what I did notice about Dawkins’ 1987 video, is that once a proximation of a word like “weasel” was attained, the mutations for particular letters seemed to slow down. This indicates to me that there might be some sort of latching going on. It may not be complete latching, as is evident in Atom’s program, but it appears that in Dawkin’s program (assuming that the video demonstration is the same program as depicted in TBW), there is some indication given that the program is nearing (or approximating) the target word, causing the mutations for a particular letter in the approximated word to slow. I can’t explain it, so it really means nothing to me, but it does seem to warrant that we know a little more about Dawkins’ program, and what is really going on.

    Did anyody else notice this? Has there been an explanation? I’m really a novice at this, so if I missed something, I apologize in advance. :)

  346. CannuckianYankee:

    You have to keep in mind what is going on ‘under the hood’ not just the observed output. At each step of WEASEL there are lots of ‘offspring’ produced, each has letters that are copied from the parent with a small chance of mutating (being randomly changed). Only one of these offspring is selected to be the parent for the next generation and the rest are discarded. This parent phrase is selected based on the number of correct letters – you only get to see this parent, you never see the population it comes from.

    When you have a population size and mutation rate in the right range the chances are that at least one of these offspring will have the same correct letters as the parent, possibly more, which will usually make it the ‘fittest’ and so it gets selected. This is how the appearance of latching happens, even though there is nothing in the code that prevents the letters from reverting – it is the effect of mutation, population and selection, and of only viewing the fittest member of each generation.

    If you could watch all the members of each generation, not just the fittest, you would see individual correct letters reverting all the time.

    If you increase the mutation rate and decrease the population you increase the probability of the fittest offspring having correct letters reverted.

    When it is running and it approaches the target phrase the rate at which letters appear to revert will drop. This is because the number of correct letters is going up but the probability of them changing back stays the same.

    It would really help if Atom added way of viewing all the members of the population, not just the fittest, because if becomes obvious what is going on when you can peek under the hood.

  347. Onlookers:

    I: It seems I have to first deal with yet another bit of unfortunately distractive objection.

    (On the ad hominem aspect: FYI above, I have and have had a life separate from wee- hours- of- the- morning engagements online, and out-of-context samples from my work in curriculum development — that’s where anything on Mechatronics comes up [I championed it as a paradigm for renewal of engineering education in the Caribbean, because of its fusion of electronics, mechanisms, and ICT's with the control mindset; BTW, the modern heavily micro-controlled car is informed by this frame of thought] — or sustainable development, or energy and development, used to try to pretend and project that I have not worn a lab coat myself (quite literally) are simply a “no true scotsman” ad hominem in disguise. And, besides the probative force of an argument comes from its weight on the merits of fact and logic, not who makes it, and what clothes s/he happens to wear [a shirtjac at the time as I recall], or when s/he said it – the just linked was a backup brief presentation for a public ethics lecture — what circle approves or disapproves.)

    On topic: the objectors above to my remarks on materialist philosophers and would-be neo-magisterium in lab coats rather than ecclesiastical robes — forgive me on this, Catholics, I have to make a point in a way that will go home to a Golden Compass, anti- C S Lewisian thinking mentality — would do well to ponder the implications of the already linked remarks on US National Academy of Sciences member Richard Lewontin’s infamous 1997 review, and the statements from the said academy in its interventions in Kansas, but moreso the following from their 2008 version of their official pamphlet on “Science” vs “Creationism” — as was also linked — which let us note, they do not directly address on the merits, choosing instead to resort to an ad hominem.

    So, let us go now to Science, Evolution and Creationism, p. 10, for the contextualised NAS definition of science and associated commentary:

    ______________

    >> DEFN (in a text box): The use of evidence to construct testable explanations and predictions of natural phenomena, as well as the knowledge generated through this process. [US NAS, 2008, p.10]

    COMMENTARY (in the just preceding paragraph): In science, explanations must be based on naturally occurring phenomena. Natural causes are, in principle, reproducible and therefore can be checked independently by others. If explanations are based on purported forces that are outside of nature, scientists have no way of either confirming or disproving those explanations. Any scientific explanation has to be testable — there must be possible observational consequences that could support the idea but also ones that could refute it. Unless a proposed explanation is framed in a way that some observational evidence could potentially count against it, that explanation cannot be subjected to scientific testing. >>
    _______________

    Now, Mr Lewontin in his 1997 NYRB review of Sagan’s Demon Haunted World (as he is a little more explicit on what is really going on there):

    _______________

    >>. . . to put a correct view of the universe into people’s heads we must first get an incorrect view out . . . the problem is to get them to reject irrational and supernatural explanations of the world, the demons that exist only in their imaginations, and to accept a social and intellectual apparatus, Science, as the only begetter of truth . . . .

    To Sagan, as to all but a few other scientists, it is self-evident that the practices of science provide the surest method of putting us in contact with physical reality, and that, in contrast, the demon-haunted world rests on a set of beliefs and behaviors that fail every reasonable test . . . .

    It is not that the methods and institutions of science somehow compel us to accept a material explanation of the phenomenal world, but, on the contrary, that we are forced by our a priori adherence to material causes to create an apparatus of investigation and a set of concepts that produce material explanations, no matter how counter-intuitive, no matter how mystifying to the uninitiated. Moreover, that materialism is absolute, for we cannot allow a Divine Foot in the door. The eminent Kant scholar Lewis Beck used to say that anyone who could believe in God could believe in anything. To appeal to an omnipotent deity is to allow that at any moment the regularities of nature may be ruptured, that miracles may happen. >>
    ________________

    On points:

    1 –> The claim that science is “the only begetter of truth,” and/or that it is the fountainhead of “knowledge” is (inadvertently) a claim in EPISTEMOLOGY — i.e. philosophy — not science. [BTW, that is part of why the earlier usage was Natural Philosophy, which then delivered "knowledge" -- "Science" is a version on the Latin for "knowledge" [which in turn is a version on the Greek!]– as its findings were confirmed as reliable and credibly — as opposed to absolutely — true. Modern usage, emphasising the “knowledge” part, too often forgets that there is an epistemological foundation for the technical work, and one with limitations as well as strengths. For instance, empirical support for an explanatory claim cannot be beyond reasonable dispute or correction in light of further findings or analysis. And in Origins sciences, explanations on the remote and unobservable past bear as well constraints that apply to any fundamentally reconstructive historical exercise; and one for which we do not have generally accepted eyewitness documents.]

    2 –> As a direct consequence, Lewontin’s remarks self-destruct spectacularly. (He makes an inadvertent philosophical claim of “self-evidence” to ground the idea that only scientific knowledge claims that pass the muster of “all but a few . . . scientists” [oops: appeal to the "consensus" view of the neo-magisterium -- and a magisterium in lab coats is but little better at resisting the temptations of error and abuse of authority than one in ecclesiastical robes . . . pardon the shock effect] provide the surest method for putting us in touch with “reality.” Consequently, his argument cuts its own throat as it “fail[s]” a decisive “reasonable test” — logical coherence.)

    3 –> Moreover, he explicitly acknowledges both a priori materialism AND ill-informed, dismissive prejudice against the idea of God, as a presumed irrational and chaotic injection into the world of thought and experiment. (But in fact, a world in which miracles are to stand out as signs pointing beyond “nature” — that which traces to chance and necessity spontaneously at work without specific “local” intelligent direction — is one in which there has to be a generally prevailing — but not watertight — orderly pattern of intelligible laws. And, historically that was precisely the mindset of the founders of modern science, with Newton as chief exemplar.)

    4 –> The NAS statement of 11 years later is subtler but makes the same core point, and falls into the same core error.

    5 –> The US NAS definition, taken in another context, would be unexceptionable. After all, I have long championed the ideal that science “at its best” is “the unfettered (but intellectually and ethically responsible) progressive pursuit of the truth about our world, based on observation, experiment, reasoned [including mathematical] analysis and discussion of results among the informed.”

    5 –> Unfortunately, there is in fact an improperly constraining, Lewontinian a priori materialism-loaded context; as may be seen from the loaded language:

    Natural causes are, in principle, reproducible and therefore can be checked independently by others. If explanations are based on purported forces that are outside of nature, scientists have no way of either confirming or disproving those explanations.

    6 –> By “nature” the NAS plainly means things traceable to forces and factors of ultimately undirected chance and mechanical necessity. (That is why it force-fits the strawmannish contrast: natural vs supernatural, in the teeth of the suppressed alternative that Intelligent Design scientists and thinkers have put forward in recent years: natural vs ART-ificial, i.e intelligent.)

    7 –> Now, the very paragraph of commentary we just extracted from constitutes an empirically observable deposit in the world of our experience; comprising 666 [believe it or not!] ASCII text characters, i.e a configuration space of ~ 2.52 *10^1,403 possible states of 128 characters. Of these, but a tiny fraction will constitute valid English language text making commentary on the NAS definition of Science.

    8 –> So, on observing certain aspects of the sequence of glyphs in front of us, we see it is: (i) readily and reproducibly observable in the empirical world, (ii) highly contingent, (iii) not readily explicable on chance and blind undirected mechanical forces, (iv) a case of functionally specific complex information. So, the ID explanatory filter points to intelligence acting through ART as the best causal explanation of the NAS paragraph, in a world where we know that intelligent agency is possible and indeed actual.

    9 –> Now, too, we have no good reason for a priori deciding that humans exhaust the set of possible or actual intelligences [Cf UD glossary on intelligence], but we may infer from the familiar case to the less familiar one.

    10 –> And, it is highly evident from such a case, that for such cases of FSCI and the like, [n]atural [INTELLIGENT] causes are, in principle, reproducible and therefore can be checked independently by others.”

    11 –> Next, it helps to observe another use of language: digital, information bearing computer code, especially algorithm-expressing instructions and associated data structures. (Again, it is quite evident that sufficiently long programs that work – i.e are physically instantiated successfully on some hardware or other — are not easily explicable in terms of undirected chance + necessity; i.e. nature acting spontaneously. That is, these are empirically observable and leave reliable, reproducible traces, but are decidedly objects of ART [techne] rather than “naturally occurring phenomena.”)

    12 –> This brings us right to a relevant case: DNA in the cells of our bodies and those of other life-forms. Here, we see digitally expressed code involving instructions, data structures and regulatory circuits, all within entities that predate human intelligence, indeed are foundational to its existence.

    13 –> So, we have here a credible case where what would otherwise be easily recognised as an ART-ifact of intelligence, is per a priori materialism in the guise of science, force-fitted into a materialistic explanation under the false colours of science, “no matter how counter-intuitive, no matter how mystifying to the uninitiated”; indeed “in spite of the patent absurdity of some of its constructs . . . in spite of the tolerance of the scientific community for unsubstantiated just-so stories . . . ”

    14 –> And, Mr Lewontin immediately explains just why: “. . . because we have a prior commitment, a commitment to materialism.”

    15 –> Nor will it suffice to say but science is only one aspect of the world of intellectual discourse . For, one of the key points is materialistic domination of the field of credibility and knowledge through captivating science to the materialistic agenda, and yes, wearing the culturally and institutionally prestigious lab coat – thus, BYW, the attempts above to defrock, read out and dismiss me. Again, Lewontin is painfully frank:

    . . to put a correct view of the universe into people’s heads we must first get an incorrect view out . . . the problem is to get them to reject irrational and supernatural explanations of the world, the demons that exist only in their imaginations [notice the conspicuous absence of reference to the issue of nature vs art, which was first seriously raised by Plato in Bk X of the Laws, c 360 BC], and to accept a social and intellectual apparatus, Science, as the only begetter of truth . . . .

    16 –> Which of course brings us full circle to the reductio ad absurdum implied by making an epistemological declaration to lock in the idea that only science is a proper ground for warranting knowledge.

    In sum, we easily see the imposition of a priori materialism on science, the operation of a lab-coat wearing materialist neo-magisterium, and its pernicious effects.

    [ . . . ]

  348. II: More on Weasel

    A] Dieb, 329: on calculating mutation rates per letter etc

    As you know, Eqn 22 on p 1055 of the IEEE paper is about the effect of latched search, with the probability of capturing a correct letter built in already in the parameters.

    Mut rate per letter is implicit in this.

    B] DNA-J, 336: can we stipulate that TBW Weasel corresponds to Atom’s Proximity Reward Search at EIL?

    Not quite as cut and dray as yes/no in absolute.

    The EIL reconstruction is of a proximity reward search that under certain circumstances of mutation rate and pop per generation, will show latching behaviour of generation champions in some runs (sometimes, a high proportion).

    The Weasel 1986 showcased o/ps as published in BW and NewScientist by Dawkins, credibly fall into that class. (The 1987 videotaped runs show (i) internal members per generation and/or (ii) an unlatched run. The first will always be so, the second will happen with other parameter settings. Dawkins’ remarks in a recent forum elsewhere suggest to me that he probably had a case of (ii), and BBC may have focused on (i) in the run, as that is where the visually interesting things are happening.)

    C] Frogbox: kairosfocus’ anti-science rhetoric shows him in a very bad light indeed, as one of those who would indeed take society back to the Dark Ages if they had the opportunity.

    unfortunate strawman distortion, laced with ad hominems. I too, as noted, am a “lab coat wearer.”

    Yesterday and today, I have specifically spoken to the corruption of institutional science by materialistic ideology.

    Please do not confuse the partyline with real world science and engineering in the trenches of the lab, workshop or the field.

    And, I have no intent to return us to dark ages of inquisitions etc – including those done by materialists under the false colours of science.

    D] Indium, 338: I have asked kf more or less the same question over 10 times now, for example in post 194 here. He will continue to avoid answering it.

    Kindly, stop prevaricating.

    I HAVE answered the question, as I just did again.

    Just, the answer on the merits is not a simplistic yes/no that neatly aligns with your rhetorical strawman.

    E] LH, 341: He spends a lot of time pontificating about herrings, oil, straw, and men.

    More accurately, I have had to speak correctively on a habitual, destructively uncivil rhetorical pattern used by darwinists, that seems to seep into the ID debates from the wider political and public relations culture. Namely:

    1] red herring distractors dragged across the track of reasoned dialogue towards truth, then

    2] led off to ad hominem soaked strawmen misrepresentations [cf the case above on the issue of natural [= the materialistic world of chance + necessity] vs supernatural as opposed to natural vs intelligent] that are

    3] ignited to create a spectacle, also clouding and confusing the air and filling it with poisonous hostility and polarisation, thence

    4] demonising and dismissing those who do not toe the materialistic partyline.

    Abundant examples — sadly — are above in this very thread.

    (And, observe how LH does not address that highly relevant fact and context, even as he indulges in yet another case in point; belittling me through a strwmannish caricature, to dismiss the well warranted correction. Sad.)

    LH and co: I would rdearly love to actually discuss the matters on teh merits; it is your consistent use of red herrings, strawman arguments and ad hominems thast forces me to remark correctively. And, the terminology is not my invention. All I have done is to chain the names for the fallacy in a way that shows the dynamical rhetorical pattern at work in distracftion/ changing the subject, distortion of concepts arguments and people, demonisation or belittling and well-poisoning as you Americans say. [We in the British-influenced world tend to think of poisoning the atmosphere of discussion.]

    It is the pattern that is destructigve and shootintg the messenger who warns of the consequences thereof is not going to stop the implications if such increasingly habitual incivility — e.g. a sitting Pesident of the USA all but names his just past V Pres opponent (evidently incorrectly on the merits) as a liar, and a Congressman blurts out “liar” to him in response on live TV before the World– is unchecked across our civilisation.

    F] I promise to forego the benefits and work product of people who teach evangelism, if you promise to forgo the benefits and work product of people who develop pharmaceutical products.

    False dichotomy, resting on a strawman.

    (And BTW, as the lead up above suggests, I have spent far more time teaching sci and tech than giving pointers on evangelism; which as a practising Christian is my right and even duty. Not to mention there is a certain little observation by a historically important evangelist that runs thusly: “What good will it be for a man if he gains the whole world, yet forfeits his soul? Or what can a man give in exchange for his soul?” [Matt 16:26] So, I would think that since material prosperity is generally speaking a good, but plainly it should not get out of hand into becoming a god; there is a legitimate place for both. [Not to mention, if you wish to forego the benefits of a culture that respects humans as having rights inherent in their being created equally by God and endowed with certain rights such as life, liberty and the pursuit of happiness [e.g. a certain evangelist named George Whitefield had more to do with motivating and grounding the American revolution than many are wont to acknowledge, and the First Congress was itself a preacher of revolution as an expression of repentant reformation and revival [cf the collection of Congressional proclamations of days of prayer, fasting and penitence or thanksgiving here, esp those of 1776, 1777 and 1779; my notes in discussion are here], you may have surprising consequences that may even prove destructive to the long term benefits of sci and tech.])

    G] CY, 345: I tried Atom’s “Proximity Reward Search” for the phrase “ME THINKS IT IS LIKE A WEASEL” several times, and each time a correct letter was attained, that letter stayed latched. Not so for Dawkins’ video demonstration of the “weasel” program.

    Vary Atom’s parameters from the default settings, which were set up to with high probability give an implicitly latched case “out of the box.”

    Try low population versions, say 5 – 10 per generation first. Then try high pop ones of 500 – 999, the max-out. Then push the mutation rate per letter high [up to 25 % or more] and low.

    H] Did anyody else notice this? Has there been an explanation?

    You are taking the right approach: look at the facts – which I have long observed is a characteristic for you. [When I see your comments here at UD, I take time to look.]

    Try App 7, the always linked. (Dawkins’ 1987 video run is probably something like a loose quasi-latched case, with a focus on the internal members of the population. On balance of evidence and claims, the showcased 1986 runs – original code by Dawkins is hard to find, hence the prize offer — were probably pretty much like Atom’s out of the box setup.)

    I] BillB, 346: When you have a population size and mutation rate in the right range the chances are that at least one of these offspring will have the same correct letters as the parent, possibly more, which will usually make it the ‘fittest’ [“the mutant nonsense [thus non-functional, i.e. fitness language is highly misleading] phrases, the ‘progeny’ of the original phrase . . . which, however slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL, ” Dawkins, BW, 1986] and so it gets selected. This is how the appearance of [implicit] latching happens, even though there is nothing in the code that prevents the letters from reverting – it is the effect of mutation, population and selection, and of only viewing the fittest member of each generation.

    With two modifications to take out loaded references, we can see that there is substantial agreement on the technical reality at such length of discussion here.

    ______________

    GEM of TKI

  349. PS: And of course the data to be explained c 1986 is precisely only viewing the fittest member of each generation the runs of generational champions (as excerpted and showcased; which is what showed evident latching]:

    ________________

    >> We may conveniently begin by inspecting the published o/p patterns circa 1986, thusly [being derived from Dawkins, R, The Blind Watchmaker , pp 48 ff, and New Scientist, 34, Sept. 25, 1986; p. 34 HT: Dembski, Truman]:

    1 WDL*MNLT*DTJBKWIRZREZLMQCO*P
    2? WDLTMNLT*DTJBSWIRZREZLMQCO*P
    10 MDLDMNLS*ITJISWHRZREZ*MECS*P
    20 MELDINLS*IT*ISWPRKE*Z*WECSEL
    30 METHINGS*IT*ISWLIKE*B*WECSEL
    40 METHINKS*IT*IS*LIKE*I*WEASEL
    43 METHINKS*IT*IS*LIKE*A*WEASEL

    1 Y*YVMQKZPFJXWVHGLAWFVCHQXYPY
    10 Y*YVMQKSPFTXWSHLIKEFV*HQYSPY
    20 YETHINKSPITXISHLIKEFA*WQYSEY
    30 METHINKS*IT*ISSLIKE*A*WEFSEY
    40 METHINKS*IT*ISBLIKE*A*WEASES
    50 METHINKS*IT*ISJLIKE*A*WEASEO
    60 METHINKS*IT*IS*LIKE*A*WEASEP
    64 METHINKS*IT*IS*LIKE*A*WEASEL >>
    ___________________

  350. KF:

    Fitness is defined by WEASEL as proximity to target, this is standard terminology for genetic algorithms, of which WEASEL is one example. It is not a loaded term, it is a standard term.

    “This is how the appearance of [implicit] latching happens”

    As we have established ALL search algorithms except a random sampler ‘implicitly latch’. Almost by definition when a search algorithm proceeds towards a target it will preserve beneficial features, in this case letters. If it didn’t then it would not be a search, just random sampling. The use of the term ‘implicitly latch’ is not useful, or part of the terminology normally used to describe this behaviour – it is something you made up.

  351. Onlookers:

    It seems I have to make a few more corrective remarks:

    1] re BB,350: Fitness is defined by WEASEL as proximity to target, this is standard terminology for genetic algorithms, of which WEASEL is one example.

    First, I must express appreciation to BB for his acknowledgement that Weasel is a [primitive -- missing link level . . . ] GA.

    One assumes BB is familiar with the phrase approved by Darwin as a synonym for “natural selection,” namely: survival of the fittest.

    He may not be familiar with the subtitle for the earlier edns of Orign before the 6th: “the preservation of favoured races in the struggle for life.”

    In that context, he will doubtless be familiar with the principle that fitness here implies that the organisms struggling to survive already have viable, functional cell-based bodies; which we now know requires some considerable degree of algorithmic complexity and a significant amount of functionally specific digital information. Also, he should recognise the contrasting points made by CRD in BW, that in Weasel, certain “mutant NONSENSE phrases” are rewarded with promotion to generational champion status because they have an increment in proximity to target. (Which BTW implies that Weasel is targetted search, another point where CRD had to acknowledge a “misleading” divergence from presumed biological reality.)

    Now, as we may see from the Wikipedia introductory remarks on GA’s:

    A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover . . . . Genetic algorithms are implemented in a computer simulation in which a population of abstract representations (called chromosomes or the genotype of the genome) of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem evolves toward better solutions. Traditionally, solutions are represented in binary as strings of 0s and 1s, but other encodings are also possible. The evolution usually starts from a population of randomly generated individuals and happens in generations. In each generation, the fitness of every individual in the population is evaluated, multiple individuals are stochastically selected from the current population (based on their fitness), and modified (recombined and possibly randomly mutated) to form a new population. The new population is then used in the next iteration of the algorithm. Commonly, the algorithm terminates when either a maximum number of generations has been produced, or a satisfactory fitness level has been reached for the population. If the algorithm has terminated due to a maximum number of generations, a satisfactory solution may or may not have been reached . . .

    We may easily see that Weasel’s use of targetted search on mere proximity that rewards non-functional entities with reproductive privileges is a key dis-analogy with biological reality — as opposed to speculations (aka theories and models) of evolutionary biologists, AND that the similar use of “fitness” in GA’s in contexts such as ours is thus highly questionable. (in short I am suggesting a reading into the thought structure of evolutionary materialistic materialistic assumptions that beg big questions on the origin of functional complexity dependent on algorithmic information.)

    Thus, my reference to loaded and misleading language is unfortunately fully justified. For, there is an issue that needs to be recognised and addressed squarely and fairly and frankly on the merits. (A question that seems to always brushed aside ever since Wistar 1966.)

    2] As we have established ALL search algorithms except a random sampler ‘implicitly latch’. Almost by definition when a search algorithm proceeds towards a target it will preserve beneficial features, in this case letters

    The little word, target, is of course highly revealing of the fundamental dis-analogy of Weasel from the real biological world, as CRD had to acknowledge:

    Although the monkey/Shakespeare model is useful for explaining the distinction between single-step selection and cumulative selection, it is misleading in important ways. One of these is that, in each generation of selective ‘breeding’, the mutant ‘progeny’ phrases were judged according to the criterion of resemblance to a distant ideal target, the phrase METHINKS IT IS LIKE A WEASEL. Life isn’t like that. Evolution has no long-term goal. There is no long-distance target, no final perfection to serve as a criterion for selection . . . In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success.

    And, insofar as other GA’s may use targets or symbolically based objective functions as metrics of relative “fitness” they are inherently a key step removed from biological reality. Similarly, if target proximity or comparison on a metric scale are used to focus on artificial selection, then the GA’s are again removed from biological reality. (Artificially selecting antennas that on empirically validated modelling, theory and simulation give better performance is one thing, begging questions over origin of functional complexity by undirected chance + necessity is another. Precisely the question being underscored by design theory.)

    Secondly, as a matter of fact — which has been demonstrated in the already linked thread — Weasel implementations do not always latch. Sometimes, we see quasi-latching [occasional slip-backs],and sometimes we see far from latching behaviour.

    That is, the issue of co-tuning of pop size, mutation rate per letter and selection on proximity to target filter are all important and non-trivial issues.

    AND, quasi-latching or even non-latching Weasels do eventually converge to target, as has been demonstrated. (Some of the runs I have seen have occasionally substituted or slipped in other ways on already correct letters. When this is rare, quasi-latching is appropriately descriptive. When it is a lot more frequent, non-latching is obviously more apt.)

    BB is simply wrong here.

    3] The use of the term ‘implicitly latch’ is not useful, or part of the terminology normally used to describe this behaviour – it is something you made up.

    BB is simply and manifestly wrong. As just pointed out, in some cases Weasels simply do not show implicit or explicit latching behaviour:

    Run C, April 9: 500/gen, 8% per letter mut rate, shows a substitution effect at line 25 in a quasi-latched, 35 gen to target run.

    Run F, 999/gen, 25% mut rate per letter, 318 gens to target, shows non-latched behaviour.

    In short — contrary to what BB imagines — the issue of latching and of related quasi-latching is explanatorily important, and the descriptive terminology is appropriate.

    And, onlookers, I don’t know of any one who has seriously studied the behaviour of Weasels and has invented a “standard terminology” that captures the observed and described ratcheting-related effects I have sought to describe and explain.

    G’day again

    GEM of TKI

  352. kariofocus, #351

    Secondly, as a matter of fact — which has been demonstrated in the already linked thread — Weasel implementations do not always latch. Sometimes, we see quasi-latching [occasional slip-backs],and sometimes we see far from latching behaviour.

    The definition of “latching” in a search algorithm is really quite plain. If a character in the search string is latched then it can not change, period. The fact that Weasel implementations do not always latch proves that it is not a latching algorithm.

    In short — contrary to what BB imagines — the issue of latching and of related quasi-latching is explanatorily important, and the descriptive terminology is appropriate.

    Any appearance of latching is simply an artifact of the probabilities defined by the initial conditions. While some combinations may make the chance of a given character changing extremely small, as long as there is any chance it cannot be considered latched. Call it “implicitly latched” or “quasi-latched” if you want but it is still not latched.

  353. Just checking in, did i win yet?

    to BillB @328: Thanks for making me snort my coffee. :-)

    KF writes> “AND, quasi-latching or even non-latching Weasels do eventually converge to target, as has been demonstrated. (Some of the runs I have seen have occasionally substituted or slipped in other ways on already correct letters. When this is rare, quasi-latching is appropriately descriptive. When it is a lot more frequent, non-latching is obviously more apt.)”

    Thank you KF, for finally (finally!) offering your definition of latching. You are observing the random behavior of multiple runs of the same algorithm, and declaring that some runs show latching but others have frequent slips and are non-latching. These runs come from the same algorithm, so you are just assigning arbitrary labels to random behavior. This doesn’t even qualify as a property of algorithms, it’s just some nonsense you made up.

    Interestingly, you (KF) now say that even non-latching Weasels “do eventually converge to target”, which seems to be a reversal of your earlier position that latching is what enables the Weasel to find the target. Maybe you should scroll up and check on that?

    KF writes> “And, onlookers, I don’t know of any one who has seriously studied the behaviour of Weasels and has invented a “standard terminology” that captures the observed and described ratcheting-related effects I have sought to describe and explain.”

    KF, clearly you don’t give yourself enough credit. With implicit/semi/quasi-latching you have invented a new terminology meaning “not a random walk”. I’m nearly certain that your Abel prize will be arriving in the mail soon.

  354. Onlookers:

    Some further, corrective footnotes:

    1 –> CT should remember that we are explaining an observed phenomenon, Weasel 1986. Its observed credibly latched o/p of generational champions may be achieved explicitly or implicitly. And, detuning of the parameters that give rise to implicit latching and ratcheting to target — or whatever descriptive terminology strikes your fancy — is a demonstrated fact.

    2 –> In short, the main issue currently on the table is not whether something CANNOT change (explicit latching) but whether it DOES not change for relevant “showcase-able” runs.

    3 –> As to “finally” offering “definitions,” CIT should be reminded that the descriptions and discussion in the relevant appendix 7, the always linked has been on the record since April, as well as onward linked runs as again linked above. And, the record of CRD’s showcased observations has similarly been on the record since 1986, as has again been replicated above: runs of generation champions that once letters go correct, they credibly remain that way, as part of a ratcheting to target.

    4 –> Since I have never equated latching and ratcheting with being targetted [and on the main problem with Weasel, it is targetting and proximity-reward search that duck the issue of functional complexity that are the key dubious points of all Weasels . . . ], it is rather strange to see CIT confusing the two.

    5 –> Similarly, the varying of parameters — as has been pointed out long since — is the key factor that drives the behaviour of Weasel algorithms that in some cases [with appropriately matched parameters] latch implicitly. Where varying parameters has a relevant and dramatic consequence, that is a material issue.

    6 –> Similarly, CIT needs to recall that what is to be explained is certain showcased results. What “good” runs do per what was deemed good “cumulative selection” by CRD, c 1986, is the empirical matter at stake. As has long since been addressed. Citing the always linked App 7:

    ____________

    >>8 –> So, we have reasonably good reason to infer that the samples above are more or less representative of the published “good” runs of what have for convenience been called generational champions, circa 1986. And indeed, since Mr Dawkins was trying to illustrate the power of “cumulative selection” to achieve an otherwise utterly improbable target, we can very reasonably conclude that the observed no-reversions excerpts of runs were reflective of and showcased what was happening at large with “good” runs. That is, beyond reasonable dispute, the good runs circa 1986 latched the o/p’s in the sense that once a letter went correct it stayed that way; as the sequence of generational champions ratcheted their way ever closer to the target, hitting it in the published cases in 40+ and 60+ generations . . . .

    12 –> To explain the latching more realistically, we may have an explicit latching algorithm based on letterwise search [that is, in effect once a letter goes correct it is explicitly partitioned off from further change, perhaps using a mask register] . . . .

    13 –> Letterwise partitioned search is also a very natural way to understand the Weasel o/p in light of Mr Dawkins’ cited remarks about cumulative selection and rewarding the slightest increment to target of mutant nonsense phrases. As such, it has long been and remains a legitimate interpretation of Weasel [i.e. c. 1986]. However, on recently and indirectly received reports from Mr Dawkins, we are led to understand that he did not in fact explicitly latch the o/p of Weasel, but used a phrasewise search.

    14 –> Q: Can that be consistent with an evidently latched o/p?

    ANS: yes, for IMPLICIT latching is possible as well.

    15 –> Namely, (i) the mutation rate per letter acts with (ii) the size of population per generation and (iii) the proximity to target filter to (iv) strongly select for champions that will preserve currently correct letters and/or add new ones, with sufficient probability that we will see a latched o/p. (This effect has in fact been demonstrated through runs of the EIL’s recreation of Weasel.)

    16 –> in a slightly weaker manifestation, the implicit mechanism will have more or less infrequent cases of letters that will revert to incorrect status; which has been termed implicit quasi-latching. This too has been demonstrated, and it occurs because an implicit latching mechanism is a probabilistic barrier not an absolute one. So, as the parameters are sufficiently detuned to make reversions occur, we will see quasi-latched cases. Sometimes, under the same set of parameters, we will see some runs that latch and some that quasi-latch . . .>>
    _______________

    7 –> Similarly again, latching or non latching versions or set-ups for Weasel are all targetted searches. Targetted searches that in Dawkins’ words reward “mutant nonsense phrases” — i.e. non-functional ones — on mere proximity to target. Thus, all Weasels show artificial selection on that which does not meet a criterion of reasonable function, build-in targets and so have added-in active information from the outset. THIS is what — as Marks and Dembski aptly analysed in p 1055 of the IEEE paper — is what explains the advantages of such algorithms over random walk searches.

    ____________

    All of these — as the excerpts show — have long since been pointed out and explained, step by step, correcting many misconceptions and misrepresentations, over weeks and months.

    The just above [and a lot of similar strawmannish commentary by Darwinists here and elsewhere on the Internet] therefore shows a remarkable, consistent failure of duties of care on the part of Darwinist critics, who should seek to understand before commenting adversely or dismissively or belittlingly.

    That is truly sad.

    GEM of TKI

    PS: And, onlookers, we see again utterly no compunctions on the exposed pattern of destructive uncivil rhetoric that I have had to repeatedly correct. We should take that evident numbness to moral considerations very seriously into our reckoning as we reflect on the state of early C21 science and society in our civilisation.

  355. Irq Conflict:

    I see your short remark on college indoctrination.

    You seem to be all too close to home.

    And that is ever so sad. (I think we need to read Plato’s Parable of the Cave, again, and think very carefully on the real world case of Socrates.)

    GEM of TKI

    _______________

    PS: I saw as well further remarks trying to imply that I am a hypocrite to point out that a seriously destructive pattern is at work. this is, sadly, more of the same turnabout accusation rhetoric. I am all too aware of my failings as a finite, fallible, fallen human being under slow and painful progress through the ethics of the gospel. That does not falsify my concerns that a pattern of destructive rhetoric based on distraction, distortion and demonisation or belittling and dismissal. Nor does it disestablish the evident facts regarding Weasel 1986. Nor does such “shut up!” rhetoric change the fact that there is an a priori evolutionary materialist neo-magisterium, duly vested in lab coats, that has clearly seized control of key science institutions such as the US NAS. Nor, does it change the fact that hey are pushing materialism under the false colours of science [even seeking to redefine "science" to suit their agenda], while actually falling into reduction to absurdity, e.g. as we see from Mr Lewontin’s “science as the only begetter of truth” — a self-refuting knowledge claim in epistemology not science. And, as Burke long ago warned: all tha tis required for evil to triumph is for good men to stand by and do nothing. So, I refuse to be silenced, strawmannised, demonised or intimidated.

    ___________

    PPS: And those who are taking “turn the other cheek” out of context above — BTW, this is specifically a Saul Alinski Rules for Radicals Communist agitator tactic — should remember that it is arguable that TWICE [and certainly at least once], the itinerant evangelist who said that, drove abusive moneychangers out of the Temple in Jerusalem, with a certain shocking implement in hand, which he plaited himself and at minimum brandished threateningly. He did it to protest abuse of key public institutions in service to powerful agendas. (In short, as SB has observed, all too many today struggle with context. Being one not easily provoked into a fight through personal insult is different from the need to challenge and correct — if necessary forcefully — public abuses publicly. [As another comparison, another famous C1 evangelist, when unjustly seized, whipped and gaoled in Phillipi, on the morrow refused to leave town quietly; standing on his rights as a Roman citizen and insisting that public wrong be publicly corrected instead of being left to spread its poison by remaining uncorrected.])


  356. PPS: And those who are taking “turn the other cheek” out of context above — BTW, this is specifically a Saul Alinski Rules for Radicals Communist agitator tactic — should remember that it is arguable that TWICE [and certainly at least once], the itinerant evangelist who said that, drove abusive moneychangers out of the Temple in Jerusalem, with a certain shocking implement in hand, which he plaited himself and at minimum brandished threateningly. He did it to protest abuse of key public institutions in service to powerful agendas. (In short, as SB has observed, all too many today struggle with context. Being one not easily provoked into a fight through personal insult is different from the need to challenge and correct — if necessary forcefully — public abuses publicly. [As another comparison, another famous C1 evangelist, when unjustly seized, whipped and gaoled in Phillipi, on the morrow refused to leave town quietly; standing on his rights as a Roman citizen and insisting that public wrong be publicly corrected instead of being left to spread its poison by remaining uncorrected.])

    Since you persist in the flawed argumentum ad nauseum ad Lewontin – who neither speaks for the whole of science nor, as far as I am aware, claims such – it seems fitting to answer the above with a famous quote from the author of the book Lewontin was reviewing:

    But the fact that some geniuses were laughed at does not imply that all who are laughed at are geniuses. They laughed at Columbus, they laughed at Fulton, they laughed at the Wright Brothers. But they also laughed at Bozo the Clown.

    Or how about this from “A letter sent to the General Assembly of the kirke of Scotland: by Oliver Cromwell Lord Generall of the army of the Common-wealth of England now in Scotland &c”:

    Your own guilt is too much for you to bear: bring not therefore upon yourselves the blood of innocent men, — deceived with pretences of King and Covenant; from whose eyes you hide a better knowledge! I am persuaded that divers of you, who lead the People, have laboured to build yourselves in these things; wherein you have censured others, and established yourselves “upon the Word of God.” Is it therefore infallibly agreeable to the Word of God, all that you say? I beseech you, in the bowels of Christ, think it possible you may be mistaken.

  357. DNA_jock

    I promise to forego the benefits and work product of people who teach evangelism, if you promise to forgo the benefits and work product of people who develop pharmaceutical products.

    You seem to be sort willing to trade your inheritance for a bowl of pottage.

    Can you image living in a society not based on Judeo-Christian values?

  358. The fact that Weasel implementations do not always latch proves that it is not a latching algorithm.

    It’s almost like saying it does not always latch until it does.

    Anyway, why the objection to latching — other than the obvious reason it destroys Dawkins point? NDE is predicated on random genomic changes being fixed, or latched, by natural selection.

  359. tribune7 wrote:

    I promise to forego the benefits and work product of people who teach evangelism, if you promise to forgo the benefits and work product of people who develop pharmaceutical products.

    You seem to be sort willing to trade your inheritance for a bowl of pottage.

    Can you image living in a society not based on Judeo-Christian values?

    Very revealing. The majority of the people in the world live in societies that are not based on “Judeo-Christian values” (I assume that you intended to exclude Islam). Many of these societies are execrable, but some are not. So, yes, I can imagine living in such a society. If you cannot, tribune7, then you must be sorely lacking in imagination, or else profoundly prejudiced.

    To answer lamarck at 344, I don’t work for a pharmaceutical company. I chose pharmaceuticals as my example, not because I know researchers who have developed life-saving drugs, but rather because I believe antibiotics represent the most clear-cut example of a public good produced by the ‘lab-coats’ that Clive was maligning. “Household Cleaning Supplies” wouldn’t have had the same impact, y’know.

  360. DNA_jock –The majority of the people in the world live in societies that are not based on “Judeo-Christian values”

    Right. And in which would you like to live?

  361. DiEb at 329:

    Where – and how – do you introduce µ (the mutation rate per letter) into eq. 22?
    Could you please calculate q(Q) for S = 500, µ=.05? Just some numerical values?
    Thanks!

    kairosfocus replies at 348:

    A] Dieb, 329: on calculating mutation rates per letter etc
    As you know, Eqn 22 on p 1055 of the IEEE paper is about the effect of latched search, with the probability of capturing a correct letter built in already in the parameters.
    Mut rate per letter is implicit in this.

    Onlookers will notice that kf fails to respond to a very simple request : “Just some numerical values”‘.
    He asserts that the mutation rate is “implicit” in equation 22. Huh?
    So equation 22 is correct, whatever the mutation rate is? What happens to the number of queries needed to reach the target as the mutation rate approaches zero?
    The fact of the matter, of which kf is painfully aware (and I mean painfully) is that eqn 22 does not take the mutation rate into account (he may or may not realize that it actually sets it at 100%) and that eqn 22 CANNOT take the generation number into account, because it cannot describe a search that uses generational champions.
    Hence all the evasion.

  362. India, or Nepal once they get rid of the communists. And thank you for asking, tribune7.

  363. India, or Nepal once they get rid of the communists.

    You mean India with the legal system based on English Common Law which at the time of its application to India was (and remains) firmly established on Christian values, right?

    With regard to Nepal, why are you confident that they will replace the communist with a pro-freedom, pro-scientific inquiry government of light and tolerance, assuming they do replace them?

  364. Mr DNA_jock,

    Onlookers will notice that kf fails to respond to a very simple request : “Just some numerical values”‘.

    You might start with a simpler query to KF-san, such as “Have you ever been wrong? Ever mismatched your socks or ended a sentence in a preposition?” Work up to mathematical issues slowly.

  365. DNA_Jock,

    So here’s my offer to you Clive: I promise to forego the benefits and work product of people who teach evangelism, if you promise to forgo the benefits and work product of people who develop pharmaceutical products.

    Do we have a deal?

    That’s a false dilemma. My point was to point out that lab coat scientism has no premium in the value of human thought. There is no such thing as lab coat thought over and against evangelical thought. The real distinction is between logical and non-logical thought (and on this a scientific training gives a man’s opinion or ingenuity or rationality no added value), for if logic goes, science goes with it. And the moral clarity that can be found (for instance from an evangelical) outside of wearing a lab coat can and should pass judgments on what lab coat wearers do, for, again, a scientific training gives a man’s opinion on morality absolutely no added value. And of course sometimes they do wrong, for they’re only human and fallible, as the rest of us are. The point is that scientism can be a dangerous philosophy, and on that anyone’s opinion, including kairosfocus’s, is just as valid as any other man’s, regardless of whether they wear a lab coat for goodness sakes.

  366. Trib and Clive:

    Thanks.

    GEM of TKI

    Footnotes:

    1] Re Sev, 356: you persist in the flawed argumentum ad nauseum ad Lewontin – who neither speaks for the whole of science nor, as far as I am aware, claims such . . .

    In fact, Seversky here is wrong.

    For, in the original remarks in my Section E the always linked, in the initial brief mentions (through links to Section E) and most recently in the expansion at 347 supra I point out the way that the US National Academy of Sciences [NAS] bases its current definition and interpretation of “Science,” AND in its interventions in Kansas c 2005 [and I gather 2001]. Moreover, this is the same position that appears in say the ACLU advice to Judge Jones, which he reproduced practically verbatim as his decision at Dover c 2005 — his much celebrated decision. (All that stuff about centuries-old rules of science.)

    So, Sev knows, or should know, that the Lewontinian a priori materialism — whether explicitly metaphysical or implicitly so through the term “methodological naturalism” — is not an easily dismissible idiosyncrasy of one man but a widespread, entrenched, instituionalised problem. Precisely what my reference to a nneo-magisterium issuing ideological evolutionary materialist edicts in the name of science (metaphorically, while wearing lab coats) is highlighting and correcting.

    2] Quote of Cromwell, 356: I beseech you, in the bowels of Christ, think it possible you may be mistaken.

    Observe, Mr Cromwell (no mean sinner himself) spoke correctively, and in Sev’s opinion, correctly. So, fallible and fallen sinners can be right, even when they speak correctively; some of the time at least. Therefore, we need to focus on the merits of any given case, rather than distractive, mischaracterising or dismissive side issues such as the above Darwinist pattern shows.

    Yes, I openly admit that like the old Protector, I am finite, fallible, and indeed fallen and under reconstruction through gospel ethics. And I have made and corrected acknowledged mistakes [e.g. my initial interpretation of Q]; including in the general context of this discussion for coming on a year now. (And Nakashima-San, you should know that before hinting as you do above.)

    Indeed, on a point from DNA-J I will do so again below.

    However, it is also objectively true that on many core matters relating to Weasel I have been correct; i.e. even fallible humans sometimes succeed in being correct after all.

    For instance, Weasel is admitted by Mr Dawkins to be targetted, artificially selected search on mere proximity to target that rewards the smallest increments in proximity for NONSENSE — non-functional — phrases. That is why Weasel is fundamentally misleading entirely apart form the credibly observed phenomenon of latching and ratcheting in the showcased runs c 1986.

    Across these months, here are some points where I have been bitterly opposed by Darwinist critics and have proved objectively correct:

    a –> That the Weasel c 1986 runs show samples of 300+ letters in which in over 200 cases — every case where a letter goes correct and could revert — once a letter goes correct in a sample generation champion, it never is seen to revert. This, in a context where it is easy to see incorrect letter values persisting for decades of generations.

    b –> That this is reflective of the import of he law of large numbers, and so it is reasonable on the observations and Mr Dawkins’ effusive remarks on the power of “cumulative selection” on the plain meaning of terms, to conclude that for the showcased runs, latching and ratcheting of correct letters in generational champions is real.

    c –> That this evidence c 1986 can be accounted for on two major mechanisms, explicit and implicit latching-ratcheting ones.

    d –> That, on subsequent testimony from CRD as reported indirectly, implicit latching best accounts for the evidence in hand from 1986. Though — and thus the focus of this prize thread — only credible code will prove actually decisive. (From recent remarks from CRD, it seems this will not be forthcoming, but he says that the general pattern of Weasel recreations out there is sufficiently good of a representation.)

    e –> That implicit latching, quasi-latching and non-latching based on runs with parameter settings that facilitate such behaviour has been DEMONSTRATED here at UD [from here on] by the undersigned on Atom’s Weasel implementation at EIL, hosted by Marks and Dembski. Ever since April 9th inst.

    f –> That the analysis on p. 1055 of the IEEE paper by M & D hinges on the observation of latching as a part of ratcheting, and enfolds in it the issue of whatever mutation rates and pop sizes may lead to implicitly latched runs. So, whatever issues may be taken with the M & D analysis or mine, latching behaviour is observable, and controls onward discussion on the point.

    3] DNA-J, 361: kf fails to respond to a very simple request : “Just some numerical values”‘.

    At 348 above, my response was:

    As you know, Eqn 22 on p 1055 of the IEEE paper is about the effect of latched search, with the probability of capturing a correct letter built in already in the parameters.

    Mut rate per letter is implicit in this.

    In short, my observationally and dynamically based point is that where we deal with an implicitly latched case [which we can demonstrate to be real], mut rate per letter, is enfolded with pop per gen and filter characteristics [which may yield implicit or explicit latching . . . i.e a mask register or the like is effectively part of a filter] and issues in the OBSERVED latching.

    Citing M & D:

    ________________

    >>Assuming uniformity, the probability of successfully identi-
    fying a speci?ed letter with sample replacement at least once in
    Q queries [in the context of a ratcheting, partitioned search] is 1 – (1 – 1/N)^Q [NB: Cf below, this DOES imply the 100% mutation rate per letter], and the probability of identifying all L characters in Q queries is

    q = 1 ? (1 – (1/N))^Q)^L (22)

    [NB: Q -- number of mutants to date; N -- number of characters in the "alphabet", L -- length of target phrase]

    For the alternate search using purely random queries of the entire phrase, a sequence of L letters is chosen. The result is either a success and matches the target phrase, or does not. If there is no match, a completely new sequence of letters
    is chosen . . . >>
    _____________

    So, the issue is to be addressed in a context of observed latching.

    4] So equation 22 is correct, whatever the mutation rate is? What happens to the number of queries needed to reach the target as the mutation rate approaches zero?

    Eqn 22 would be correct on the premise that latching behaviour is OBSERVED, and the particular features of the M & D illustrative model (i.e. the context for their discussion) are followed. Latching, in turn depends on a matching of mutation rate per letter to pop size and to filter characteristics.

    This is pivotal.

    Mut rate –> 0 or –> 100% are cases where diverse effects will happen depending on pop size and filter characteristics. One of these will be that under certain circumstances latching will be lost one way or another.

    (For instance if pop per generation size = 1 [to make the point obvious to all] or only a few, with a low but non-zero mutation rate, reversions will predictably appear — so latching will vanish — as there will be insufficient population per generation at the mut rate to reasonably assure observability of no-change cases. It is the highly reliable presence of the no-change cases that acts with the filter to lock in [ = latch] progress to date. The presence of a sufficiently — but not “too-” — high mut rate is required to get single-step progress to target. With a too-high mut rate, multiple letter effects such as substitutions will occur, leading to reversions and parallel advances, again destroying latching. In short, the issue is that the analysis is on the premise that latching must be observed and to be observed must be based on certain dynamics, whatever errors may or may not be present otherwise in the M & D analysis. [Yes, M & D use a simplistic illustration of what partitioning means, and do so in a way that invites dismissal of what they analysed. Yes, they look at a case where for illustration, every letter is changing in the envisioned generation champions, and this produces obviously implausible single generation advances -- 5 letters -- in their constructed example. Yes, one can construct a strawman algorithm from this which will not resemble Dawkins' "algorithm"; howbeit M & D also host a recreation of a wide range of possible Weasel algorithms and display their comparative effects, indeed going on to analyse some to these in later sections. And, Mr Dawkins has not provided actual code or a technical summary of his algorithm[s] so various possibilities are credible or at least legitimate on the relevant evidence.])

    5] eqn 22 does not take the mutation rate into account (he [KF] may or may not realize that it actually sets it at 100%) and that eqn 22 CANNOT take the generation number into account, because it cannot describe a search that uses generational champions.

    I have shown that generation number for a proximity reward search case — which under certain conditions will implicitly latch — can be accounted for on simply reckoning that Q comes in generational lumps of size S. In G generations, of size S, Q = G * S. (And so, on any given mut per letter rate etc, there will be Q queries at any given time, but say it will jump in lots of 50. And if in any given lot of 50 the correct phrase appears, the Weasel will of course pick it up. And if any advance appears, it will be recognised.)

    Now, you make an intersting point, that in the model in Eqn 22, the implied per letter mut rate on unlatched letters is 100%, which is of course the pattern they illustrate with their example.

    Now, since I have focussed hitherto on the empirical data and dynamics of variable mut rates and the appearance of latching as a control, I have based my view of what was going on on this; which is an objective external control above and beyond the mathematics involved. (Such a control, BTW, limits the effect of errors one may make in a logical analysis. that is why the Galilean principle is correct and helpful: ideas must be subject to empirical tests. And, that is why even though his explanation of tides etc was rather plainly wrong, we today reckon that Galileo had the better of the case on balance regarding whether the Copernican scheme was more or less correct.)

    In a 100% mutation per letter rate situation of course, implicit latching will be practically impossible — especially with a pop size of one per gen. So, the didactic model would at once fall apart if it were to be attempted practically. [That means, practically, it CANNOT be a real world case on proximity reward search. I do believe it would in general work on explicit latching, though getting a five letter increment in proximity to target on a single member generation model is rather unlikely adn would not be typical behaviour. M & D are most likely giving a didactic illustration, not a credible actual run.]

    Where I went wrong.

    Now, let’s look at the probability on a particular letter position going correct that M & D use: {1 – (1 – 1/N)^Q}. The second component is that odds of not being correct are (1 – 1/N)^Q, i.e. Q independent tries on (1 – 1/N). This last is odds on not being correct on a uniform distribution on N states. And you are correct, this is indeed implying 100% odds of change on the letter per generation-member.

    I stand corrected on this.

    And, the case will not be observable on a proximity reward case without explicit latching, as a 100% mut rate will impose in praxis non-latched non-ratcheting behaviour. Implicit latching and ratcheting are are observable, but not credibly on the terms discussed on p. 1055.

    However, using odds of selection for mutation per letter, s, brings to bear the analysis in App 7 point 18 on, e.g.:

    A letter in the string of length L [= 28] has probability of being selected to mutate, s. Once so selected, it can equally take up any of the g [= 27] available states at random. Of these, one is identical to the original state and 26 are changed outcomes. So, we can see that, for a given letter:

    chance to be NOT selected = 1 – s

    chance to be selecd but not change value = s * 1/g

    overall chance to remain the same = (1 – s) + s/g

    chance of no-change for a string of L letters = [(1 - s) + s/g]^L

    [Odds of at least one change being of course the probabilistic complement]

    In short, the M & D model in part E of the paper is correctable in principle.

    The analysis in part F of that paper points the way [I forget who said that, he is correct], with the proviso that population size and mutation rate actually need to be matched, as beyond a certain limit, substitution effects etc. will tend strongly to do away with latched, ratcheting behaviour also. (Also, demonstrated.)

    6] Nakashima-San, 3564: “Have you ever been wrong? Ever mismatched your socks or ended a sentence in a preposition?” Work up to mathematical issues slowly.

    You have a point, given what I have acknowledged above; on taking a closer look at the model M & D presented in Eqn 22.

    I do not and have not claimed infallibility, however I do maintain that empirical controls do limit error, as I also highlighted. (And in that context, I think it is also fair comment that there are several specific points [cf. above] where — despite rather strident criticism — I have been right. Right in ways that strongly limit the impact of limitations of Eqn 22. And, the pattern of destructive rhetoric I have spent much of this thread addressing is real and needs to be corrected.)

    7] On Judaeo-Christian heritage.

    I think many of us have been indoctrinated into thinking that does not accurately or fairly reflect the actual balance or key foundational role of the historical contribution of the Judaeo-Christian frame to our civlisation, not only on law and morality and liberty etc, but on even the rise of science. (Cf Peterson’s introductory discussion in the context of the ID debate, here.)

    ___________

    So, the above includes not only points where I think I am right, but a key point where I have been wrong and set out on correcting that error.

    GEM of TKI

  367. Following up:

    Let’s see what an adjusted form of the M & D analysis could look like; again in the context of OBSERVED latching.

    1] Each letter has N states, which we may take the “odds” — I am using this loosely for probability — of being selected on any try as s. If so, on a default, uniform distribution, odds of being selected and going correct on any mutant phrase would be:

    s* (1/N) = s/N

    [For s =1, s/N --> 1/N, the case that M & D seem to have analysed]

    2] Complementing, the odds of not being selected and/or not going correct would be

    1 – s/N

    3] With Q independent tries,the extended complement becomes odds of not being selected and/or not going correct after Q tries:

    (1 – s/N)^Q

    4] So odds that somewhere in the Q choices a letter will be selected and will go correct are the second tier complement:

    [1 - (1 - s/N)^Q]

    5] For L independent letters, this extends:

    [1 - (1 - s/N)^Q]^L

    6] Now, to get to “catch and keep,” we first allow Q to increment by generations of size z, so in G generations, we see Q = G*z

    7] Then, the odds of L letters going correct in G generations would seem to be (under “catch and keep” constraints to be discussed following):

    q ~ [1 - (1 - s/N)^{G*z}]^L

    8] Obvious limitation — need to catch and keep. That is, this extension of the M & D analysis implies that if a letter goes correct it must be caught and kept, i.e. there is a generational sparseness but observability of go-correct mutations such that no more than one letter changes to go correct per mutant as a rule, and that the pop is of scope that once one correct mutation appears, it will be captured. In the meanwhile, the pop should be of sufficient size for the rate — which needs to be small enough too — that no-change cases are overwhelmingly likely to be present. that way, we don’t have a holed keep-net.)

    9] This boils down to saying that the already identified plausible and empirically observed conditions for implicit latching must be met if this simple extension to M & D is to work. [Note that approximation rule: ~ not =.]

    10] under such circumstances it seems likely enough that we will see cases of implicit latching of the generational champions, and that selection of such to showcaswe will be a feasible action, especially iof per Weasel 1986, one is looking for “good” examples of “cumulative selection.” Where, “cumulative” normally means: Increasing or enlarging by successive addition.

    11] Which was what was to be explained, per showcased run excerpts circa 1986.

    _______________

    So, let’s see what others have to say . . .

    GEM of TKI

  368. kairosfocus, it’s gratifying to see that some progress is being made in this debate — a rather rare occurrence on this forum. But issues still remain.

    Across these months, here are some points where I have been bitterly opposed by Darwinist critics and have proved objectively correct:

    From what I can tell, each of the points in your list has either not been disputed, or is in fact incorrect. We can go through each point individually if you’d like.

    Eqn 22 would be correct on the premise that latching behaviour is OBSERVED, and the particular features of the M & D illustrative model (i.e. the context for their discussion) are followed. Latching, in turn depends on a matching of mutation rate per letter to pop size and to filter characteristics.

    This is pivotal.

    Mut rate –> 0 or –> 100% are cases where diverse effects will happen depending on pop size and filter characteristics. One of these will be that under certain circumstances latching will be lost one way or another.

    Of course Eq. 22 is correct given the particular features of M&D’s model, since eq. 22 is derived from those features, which include explicit latching. Explicit latching clearly does not depend on a matching of mutation rate to pop size, as it includes an added mechanism that shields correct letters from mutation.

    Nor does implicit latching depend on a matching of mutation rate to pop size. The higher the pop size, the lower the probability of losing a correct letter. And the lower the mutation rate, the lower the probability of losing a correct letter. No matching is necessary. If you don’t believe it, we can work through the math. If you’re claiming that latching will be lost as the mutation rate goes to zero, you’re wrong.

    Yes, one can construct a strawman algorithm from this which will not resemble Dawkins’ “algorithm”

    The algorithm described textually and mathematically in section III.E of M&D’s paper clearly contradicts both the description of WEASEL and the results thereof reported in TBW. The strawman algorithm is of M&D’s making. If you think that someone here has strawmanned M&D’s strawman algorithm, then tell us how.

    And, Mr Dawkins has not provided actual code or a technical summary of his algorithm[s] so various possibilities are credible or at least legitimate on the relevant evidence.])

    The algorithm described by M&D in section III.E is not a possibility, as it contradicts Dawkins’ description and reported results.

    Now, since I have focussed hitherto on the empirical data and dynamics of variable mut rates and the appearance of latching as a control, I have based my view of what was going on on this; which is an objective external control above and beyond the mathematics involved. (Such a control, BTW, limits the effect of errors one may make in a logical analysis.

    Your position has been shown to be false by both the mathematics and the empirical results, so the above statement rings rather hollow.

    I’ll comment on your extension of M&D’s math later.

  369. kairosfocus:

    If so, on a default, uniform distribution, odds of being selected and going correct on any mutant phrase would be:

    s* (1/N) = s/N

    Couple of problems I see here.

    Big problem: The probability of a given letter going correct on any mutant phrase is 1/N only if you assume a 100% mutation rate. But that assumption would contradict your assumptions in #8.

    Not-as-big problem: P(A&B)=P(A)*P(B) only if the two events are independent. Obviously, getting selected is not independent of the given letter going correct. This can be remedied by defining s as “the probability of this sequence being selected given that the letter in question went correct”.

    But s is also dependent on whether other letters in the sequence went correct, and also on whether letters in other sequences went correct. The upshot is that I see no way to define s such that all of the steps in your derivation are true. Maybe you can see a way.

    Setting aside the problems in the derivation, we can easily see that your conclusion is not true. Consider that we can make the mutation rate arbitrarily low and still meet the conditions stated in your #8. Your conclusion says that q should remain constant as the mutation rate drops ridiculously close to zero, but we know that q would, in fact, also decrease.

    If there’s anything wrong with my take on your math, I’m open to correction.

  370. KF-san,

    Sir, I honor you. Keep up the good work.

  371. –kf

    As you know, Eqn 22 on p 1055 of the IEEE paper is about the effect of latched search, with the probability of capturing a correct letter built in already in the parameters.

    In #123 you stated:

    Again, once the run of generational champions takes on the cumulative progress, ratcheting-latching pattern [and cf the showcased runs of 1986 on that], it makes but little difference whether it is produced explicitly or implicitly.

    In #222 you described a proximity reward search with a population of 500 and a mutation probability µ of .04 as implicitly latched.

    So, according to you, eq. 22 should apply. I just ask you to do the actual math, and to calculate the values. This should not be that complicated, should it?

    Could you do the math, please, with S=500, and µ=.04?

    P.S.: I’d take it as a personal favour if you could start your answer with the sentence: Yes, the value is … and No, I couldn’t calculate the value. After this, feel free to elaborate.

  372. Okay:

    After an 8-hr power cut last night since before midnight and dodgy net connexions since [hope this is not a hint from "someone" on the likely prospects of the new Govt . . . "Mons'rat lack arf" is not a joke if/when it moves from song to reality!], a few footnotes:

    1] Rob: Nor does implicit latching depend on a matching of mutation rate to pop size. The higher the pop size, the lower the probability of losing a correct letter.

    This underscores the importance of a dynamical-empirical view rather than a principally mathematical one.

    Once pop size goes up enough, implicit latching is lost the other way: far tail effects such as substitutions [one reverts, another advances] — also demonstrated [cf line 25] — show up.

    Hence too the importance of the law of large numbers here in making relatively improbable “far tail” or “black swan” events observable as sample size goes up.

    2] The algorithm described textually and mathematically in section III.E of M&D’s paper clearly contradicts both the description of WEASEL and the results thereof reported in TBW.

    M & D do not describe an algorithm, they give an unrealistic illustration. It seems that given the rhetorical environment it would have been better to have given an actual run showing implicit latching and ratcheting.

    Recall, such exist and have been demonstrated, since April.

    3] Your position has been shown to be false by both the mathematics and the empirical results

    In fact implicit latching has been empirically demonstrated, ever since April 9th, as has repeatedly been underscored [and as was just linked]; whatever debates may be had over mathematical models and errors regarding thereof; the dynamical-empirical framework is valid.

    And, once implicit latching has been shown, it is a credible explanation of the showcased runs of Weasel 1986.

    Also, on the mathematical side my issue was that I misread a term in an equation. (BTW, it seems that you, too, seem to have done so; cf. below.)

    Once I saw that I did, I acknowledged that and provided an alternative that fits with the relevant regime. I see you challenge it, so I comment:

    4] The probability of a given letter going correct on any mutant phrase is 1/N only if you assume a 100% mutation rate. But that assumption would contradict your assumptions in #8.

    N states for the L relevant characters, prob of being selected for mut s; on flat random model, odds go to essentially s/N.

    (Independence is effectively true: each letter is picked in succession, and once it is in the hopper the s-odds die is thrown; deciding whether or not to let it take up any of the N available values at random. then, next letter. With odds of say 4% or so, typically one letter per 28-letter phrase will be varied, and 1 in 27 times it will repeat itself. And with a big enough but not too big pop, there will be to high odds no-change cases or at lest no distance to target change cases, and when a change occurs that goes closer home, it is likely to win. If pop is too big, multiple mutaiton effects will be more likely to pop up, and when a correct letter reverts while another advances in the same pop member, then this may crop up in the gen champs line, which would break the latching effect. Such substitutions were also demonstrated, as can be seen here in line 25.)

    note again: I have also in effect inferred that we look at any given letter, say: l; then roll the dice to see if it will be permitted to mutate to one of 27 states, with s being odds that the given letter will mutate.

    Then the next letter is fed in etc.

    5] Consider that we can make the mutation rate arbitrarily low and still meet the conditions stated in your #8. Your conclusion says that q should remain constant as the mutation rate drops ridiculously close to zero, but we know that q would, in fact, also decrease.

    Where did this come from?

    In the analysis above, at 367, I am using q analogous to M & D for their s = 100% case. [I have already noted that s = 100% is not a practically feasible case to have implicit latching. I note that due to the required matching to get implicit latching, which was demonstrated, s is indeed factored in once we see latching. I simply misread the full import of M & D's 1/N; this I have adjusted on seeing it, for he relevant implicit latching and ratcheting to target case: catch and keep in effect all cases where letters go correctt he first time. ]

    That is q is NOT a constant but the odds of going correct after G generations of size z. Thus, since s is a variable which will affect a rather large exponentiation, s will affect its value as it falls.

    Indeed at s = 0, q will be zero independent of G; save for the trivial case where the initial string is the target. As s –> 0, q for a given G will fall towards zero, and that will be in the context of a probably large Q = G* z.

    Which is what the intuitive expectation is too.

    (And I think this all shows just how hard it is to “read” these eqns right, on all sides.)

    6] Nakashima-san:

    Appreciated.

    I guess I need to go off and do 500 lines of serious derivation as due penance to the gods of mathematics . . . ;)

    However, the dynamical-empirical fundamentals of Weasel and why implicit latching is a credible account for the showcased runs c 1986 remain the same. (And that is why I rely on and prioritise dynamical-empirical methods.)

    GEM of TKI

  373. PS: I may need clarify what I mean by no-change cases: members of a pop of mutants that are equal to the seed for the generation. With pops of reasonable size and low enough mut rates per letter, they are very likely to be present. So they are the latching backstop: another mutant is likely to be chosen by the gen champ selecting filter only if they preserve the existing letters AND add a new one. Failing such, the no-change case passes through to be the next gen champ. And in fact the two 1986 showcased runs hit target in 40+ [with 3 initially correct letters] and 60+ gens, indicating that about 1/2 the time no-change members won the contest to be seed for the next gen. [This is of course discussed in my App 7 the always linked. (I confess I get the distinct feeling that a lot of critiques are in a context of having never read what I actually have to say step by step on the matter.)]

  374. PPS: For a more technically sophisticated version:

    1] Bayes Th:

    p(A|B) = p(A AND B) / p(B)

    2] Here, what I have given as probability of going correct is actually in context prob of going correct on being selected:

    p(K|S) = 1/N,

    –> where N alternative values for a given character are possible (here, 27) and there is no reason to prefer any one value relative to the rest

    –> of these N values, one is correct

    –> in the case of potential implicit latching, each letter in turn for a member of a pop is subject to selection and if chosen, will take up one of N values at random, one of these being correct relative to the “distant” target. [This is of course at he heart of the dis-analogy between Weasel and real life as CRD acknowledged in BW.]

    3] We are interested in the probability of being selected AND being correct:

    p(K AND s) = p(K|S) * p(S)

    –> Where p(S) = s, by definition, i.e. the per letter mut rate.

    –> And we see already that p (K|S) = 1/N

    4] So, substituting and rearranging:

    p(K AND S) = (1/N) * s = s/N

    –> this is the result presented more loosely above.

    –> And, it is why I said the probs are ‘effectively” independent. (I am aware that conditional probability and Bayes th etc are even harder to think through. Cf my discussion in App 6 on Caputo et al . . .)

  375. PPPS: And of course weirdly enough for s = 1, it turns out that we see 1/N. (But the case is artificial, as an implicitly latched version would be practically — with probability, almost anything is logically possible but some things are practically impossible — impossible and an explicitly latched version would be utterly unlikely to run as illustrated. That is the M & D example is most credibly by way of illustration, not a credible actual run. And of course we should reckon with the implications of the multiple algors at EIL. There is no THE M & D algorithm to be contrasted to a “THE” Dawkins algor. [Indeed, it is now quite clear that here will be no fortcoming c 1986 Weasel code; absent such code, we do not know the actual state of the algors c 1987 beyond all reasonable dispute; so various interpretations of Weasel c 1986 have a certain degree of legitimacy, and indeed that is so despite statements and declarations made in subsequent years. A declaration is not a demonstration, especially when it is made after the fact of a debate challenge and the decisive evidence is not forthcoming.])

  376. [ .. ] an explicitly latched version would be utterly unlikely to run as illustrated. That is the M & D example is most credibly by way of illustration, not a credible actual run.

    Utterly unlikely? I don’t think so! And if you asked W. Dembski and R. Marks, I’m sure they’ll tell you that the example wasn’t constructed, but an actual run of some program. Of course, they may have discarded some runs without any (new) correct letters in the first two generation (the most probable events) – but their example is more probable than getting firstly a queen and secondly a black two from a deck of card.

    But I suppose you’ll tell me that drawing the queen of hearts and then the two of spades is utterly unlikely and not a credible actual run of the game of drawing two cards.

  377. This is fun.
    This has to be the slowest derailment I have ever watched.

    kairosfocus at post 66

    23 –> however, on p. 1055, they simply describe, exemplify and analyse a partitioned search.

    kairosfocus at post 372

    2] The algorithm described textually and mathematically in section III.E of M&D’s paper clearly contradicts both the description of WEASEL and the results thereof reported in TBW.
    M & D do not describe an algorithm, they give an unrealistic illustration
    [Emphasis DNAJ's]

    Expedient, but wrong. You were correct at post 66, but since then you have had to concede that the partitioned search they ‘described, exemplified, and analyzed’ is quite different from TBW Weasel. Hence the evasion.
    So now, according to kf, there is no “THE” M&D algorithm in Section E, just an unrealistic illustration – Huh? So what are they calculating the active information for?

    As the train ever so slowly comes off the rails, kf has learnt that eqn 22 can be simply modified to take into account mutation rates other than 100%. Now would be a good time to re-read posts 34, 114, 164, and the first half of 305.
    With s/N replacing 1/N in eqn22, do some exploring. You still cannot get a partitioned search that looks like the TBW run.

    kairosfocus at post 375

    PPPS: And of course weirdly enough for s = 1, it turns out that we see 1/N.

    That’s not really “weird“, it is the starting point, and the algorithm that M&D explicitly describe. With Math. And it CANNOT be Weasel.
    More importantly, equation 22 cannot be modified to take generational champions into account. When DiEb asks you to “just show me some values”, he is gently trying to show you that your Q = GenSize x Gen# approximation leads to results that are waaaay off. I can help you here: You have showcased a run of 21 generations, where Q = 999 x 21 = 20,979, with a mutation rate of 8% (your run D). According to your math (post 367)

    q ~ [1 - (1 - s/N)^{G*z}]^L

    the probability that this search is not finished within the first 11 generations is 1 in 5 million million. Try it at home:

    q ~ [1 - (1 - 0.08/27)^(999*11)]^28

    My computer returns zero if I try to put a number >12 into this equation….

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