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Dodgen Daily

In a post a couple of days ago I asked the class to discuss a little computer program designed to “illustrate” natural selection.  Of course, the class jumped all over it and easily demonstrated how ludicrous the program’s assumptions were.  That day I got the following emai:

First, let me agree that the simulation does [not?] make a good case for RM&NS, but that is because the simulation itself is poor.  One of your more astute commentators makes the comment that intermediaries should themselves be words, to be ‘viable as life’.  This can be done. Zachriel . . . has a very good simulation that will do that. http://www.zachriel.com/mutagenation/ 

XX

I am just a humble lawyer, so evaluating Mr. X’s claim that this simulation really is as “golly gee whiz right on the money” as claimed is beyond my ken.  So I asked Gil Dodgen, UD’s resident programing expert, to review the program and give me his take.  His kind reply is below. 

I downloaded the simulation and looked at the source code. It is written in a programming language with which I am extremely familiar because I used it to develop the mission planner for our company’s guided airdrop system. I had to chuckle.  The program takes a “seed” word and randomly alters it in a variety of ways, then searches a 100,000-word dictionary, loaded into RAM to facilitate the efficiency of the search algorithm. If the altered character string is found in the dictionary it is preserved in an array, awaiting further alteration, otherwise it is discarded. 

The dictionary is probed with a binary search, which works as follows: The entries in the dictionary are presorted in ascending numerical order. A binary search, seeking a match in a presorted array, looks at the middle. If the value being sought is less than the value found in the middle, the top half of the array is ignored, only the bottom half is considered, and the search looks in the middle of it (or the bottom half is ignored if the value being sought is greater than that found in the middle of the array). This process is repeated until a match is made or it is discovered that the sought-after data does not exist in the array. A binary search takes advantage of the fact that the database is already sorted. 

Binary searches are extremely powerful and efficient, assuming that the database in question has been presorted in ascending or descending numerical order. A presorted database with 2^n entries can be exhaustively searched with a maximum of n probes. Since 2^32 is 4.29 billion, a presorted database with more than four billion entries can be searched with a maximum of 32 probes. 

Using a binary search on the presorted 100,000-entry dictionary included in the program, a random string can either be found or discarded with a maximum of 17 probes of the RAM-based dictionary (2^17 is greater than 100,000). 

The bottom line: This program is a joke, just like Dawkins’ Weasel program. In the Weasel program a prescribed letter in a prescribed location in a prescribed character string is conserved when a match is made. In the case of the Zachriel program a prescribed word in a prescribed location in a prescribed English dictionary, presorted to effect an efficient binary search, is conserved when a match is made. Weasel and Zachriel are essentially identical concerning matching and conservation, but Zachriel requires more sophisticated programming techniques. 

None of this has anything to do with biological Darwinian evolution. 

By the way, if you want to defeat Zachriel just enter a long random string containing only consonants. 

Gil 

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31 Responses to Dodgen Daily

  1. The weasel keeps popping up in many guises!

    It should be noted that the famous Nilsson and Pelger simulation that evolves an eye is another example of a program that simply performs a trial and error process to get to a predefined goal. Dawkins embarrassed himself by cheerleading for this program in an article back in 1994 (Nature, Vol 368, 21 April 1994).

    Avida is also just a more sophisticated example of the weasel algorithm.

  2. StuartHarris writes: “Dawkins embarrassed himself . . .” This assertion assumes the premise that Dawkins retains the capacity for shame, a premise that is increasingly suspect.

  3. I also looked at that program by Zachriel and came to a similar conclusion. The only good thing that program is good for is defeating the weak claim that such processes cannot generate limited increased complexity at all (a horrible argument if you are an ID proponent). I’ll see if I can find that old email where I ponder a version that would more accurately reflect the biological reality.

  4. From what I understand the Nilsson and Pelger computer simulation of the evolution of the eye never even existed! See this article by David Berlinski:

    http://www.discovery.org/a/1416

    It was all apparently wishful thinking on the part of Dawkins, and thus a rumor and a legend began.

    From the article:

    Whatever the merits of computer simulation, however, they are beside the point in assessing Nilsson and Pelger’s work. In its six pages, their paper contains no mention of the words “computer” or “simulation.” There are no footnotes indicating that a computer simulation of their work exists, and their bibliography makes no reference to any work containing such a simulation.

    Curious about this point, I wrote to Dan-Erik Nilsson in the late summer of 2001. “Dear David,” he wrote back courteously and at once,

    You are right that my article with Pelger is not based on computer simulation of eye evolution. I do not know of anyone else who [has] successfully tried to make such a simulation either.

  5. [...] UD critiques Natural Selection program [...]

  6. In the video interview of David Berlinski, “The Incorrigible Dr. Derlinski”, he says that any simulation of evolution that appears to work doesn’t use Darwinian processes, and those that use Darwinian processes don’t work.

    This is an example of the latter. Is anybody familiar with it? And is it biologically accurate?

    [url]http://www.mutationworks.com/rdmc/index.cfm[/url]

    (If the link didn’t work, I have revealed myself as a newbie. I would appreciate being corrected if it didn’t. If it did work, please ingore this, because I don’t want to reveal myself as a newbie.)

  7. wow…..so i know that evolutionists pretend that all of this is much ado about nothing….but has anyone actually come up with helpful programs to roughly simulate what evolutionists claim? it seems fairly important if they are going to maintain credibility in the longterm…

  8. How is the simulation valid if it uses a dictionary to validate a word?

  9. 1. I find Zachriel’s simulation to be much more valid than Dawkins’. That said, if I understand correctly, any mutation that produces a “word” that is found in “the dictionary” is kept. Though the need to make “logical” mutations is valid, the resultant sentance must always be valid, and, at least in some reasonable context, be at least as valid as the pre-mutated sentance. Zachriel has come a long way to making a valid simulation. He just has a long way to go yet.

    2. The real world doesn’t behave this way — adopting everything that might work. A prime example is pentadactilism. All quadruped species living today have five or less digits per limb. That dispite the fact that humans, cats, mice and dogs have all demonstrated periodic polydactilism. The polydactile versions show no obvious deleterious characteristics, they pass polydactilism on to their children, and achieve polydactilism with a single point mutation. If Zachriel’s algorithm is correct, then the polydactile model should be regularly tried, and should periodically stand out as the norm for species. Conclusion — nature rejects pentadactilism for reasons that have nothing to do with Zachriel’s simulation.

    3. Interested, “has anyone actually come up with helpful programs to roughly simulate what evolutionists claim?” I haven’t seen one. Its actually rather hard to do. How do you determine “survivability” within the simulation? How do you allow the definition of survivability to be dynamic? It would be quite a feat to produce a truly valid simulation of RV+NS.

  10. bFast:
    Zachriel has come a long way to making a valid simulation.

    A valid simulation of what? Certainly not biological evolution. I could write a program that generates 100,000 random numbers within a certain range, sort them, and store them in an array, then use a random process to generate numbers within that range and check to see if they are in the original database. What would that demonstrate?

  11. bFast: “Zachriel has come a long way to making a valid simulation.”

    Of what exactly? What about his simulation is analogous to anything with regards to DNA, genes, gene expression, proteins and their interations, and the dynamic evolution of such that leads to novel features?

  12. If anything, in his demo, Zachriel validates the ID claim that there is a tight parallel between the written English language and the language of DNA. He validates the, “each mutation must make sense” position taken by Behe, Denton and others.

  13. It should be noted that such search methods are faster than a blind search. The design of the selection filter also plays a huge part in how capable they are.

    1. “methinks like a weasel” approach
    2. Zachriel approach. Words must be full words to have any fitness. Use point-mutations and insertions in cross-over. Strings can be de-selected.
    3. Set the fitness of a word to the length of the word in letters if it is a valid word, 0 elsewise.
    4. Fitness of the word is determined by length and whether any letter out of 10 matches ANY word. (Example: “nxxcxxxxxsx” is selected for matching “narcissism”). Letters selected as matching a word can still be randomized in the next iteration, so a match can be made with a different word.
    5. Assuming ASCII, fitness of the word is determined by length and the absence of any non-alphabetical characters. As in, fitness is 0 if the generated string contains any character outside of the 52 English alphabet characters (26*2 considering upper and lower case).

    As a filter, they’re listed from “narrow” to “broad”. I’m sure I could think of more. Point is, 1, 2, and 3 are more likely to produce results. 4 and 5 still use Darwinian mechanisms but aren’t designed as well as the top two. Someone did try out method 4 for a 100 iterations, and it never found a true word of any significant length – in fact since there was no limit to the number of characters that could be included in a string, many of the character strings exceeded 100 letters, but were just pure gibberish from an English point of view.

    Depending on the design of the GA there appears to be a complexity threshold that can be reached. This is primarily determined by the environment and the constraints imposed on the randomize and fitness functions. Earlier on UD I challenged a Darwinist to refine a GA so that it could produce 500 informational bits (a requirement to be considered CSI). If I remember correctly he was stuck around 80 informational bits. I suggested several other approaches for his GA. Designed correctly, I wouldn’t be surprised if his program could eventually reach 500 informational bits. But those designs are likely to incorporate obvious front-loading where as a more generalized approach is likely to stay stuck.

    GAs are not general purpose. They have to be crafted with a purpose and constrained within certain parameters in order to reach the goal. Biological reality often has very little to do with the refined design of GAs which are more like automated “trial and error” programs. What this program does tell us it that Intelligence combined with Darwinian mechanisms can produce results in artificially constrained environments…but that does nothing to alter biological reality. So as we learn the limitations of GAs we might learn more about the limitations of Darwinian mechanisms acting on biology.

    In the past on UD I’ve also noted my belief that in special scenarios under certain conditions IC/CSI “might” be produced within biology. (I say might since I haven’t seen this occur with CSI yet. And apparently Behe’s paper shows this to be the case with limited forms of weak 2-3 component IC.) When a certain threshold of complexity is reached via design it may be possible for additional “emergent complexity” to be generated depending on how the system was designed (plasticity in the language and the formulation of base classes of information). I know Bill thinks that CSI cannot come about in such a manner but what if under VERY limited circumstances it can? If that’s the case it might be a good idea to develop a “fallback position” in the literature, just in case there are very limited instances where CSI can be generated inside an already complex system without intelligence. Instead of being seen as “scrambling to cover our butts” we’d just just point to the literature and say “this wasn’t completely unexpected”. In that case the design detection methods would have to be refined to account for these limited instances.

  14. THE OTHER SIDE RESPONDS TO GIL:

    Quote (franky172 @ Nov. 01 2007,10:51)

    But Dodgen has moved the goalposts – the author of the e-mail didn’t want ot simulate biological evolution – he wanted to show that RM+NS was an effective search strategy – which he did.

    Word Mutagenation was originally inspired by a comment from Sean Pitman over at the newsgroup talk.origins.

    Quote

    Sean Pitman: Just try a little experiment yourself. Start with a short 2 or 3-letter word and see how many words you can evolve that require greater and greater minimum sequence requirements. No doubt you will quickly find yourself coming to walls of meaningless or non-beneficial potential options that separate you from every other meaningful and beneficial option.

    Recently, Dembski has posted an unpublished draft paper on what he calls “Active Information”.

    Quote

    Dembski: Such assumptions, however, are useless when searching to find a sequence of, say, 7 letters from a 26-letter alphabet to form a word that will pass successfully through a spell checker… With no metric to determine nearness, the search landscape for such searches is binary—either success or failure. There are no sloped hills to climb.

    Incredibly, Dembski repeated Pitman’s debunked claim.

    Quote

    GilDodgen: I downloaded the simulation and looked at the source code. It is written in a programming language with which I am extremely familiar because I used it to develop the mission planner for our company’s guided airdrop system.

    GilDodgen used VBasic for development?! Anyway, most of GilDodgen’s analysis concerns the spell-checker (3 paragraphs).

    Quote

    GilDodgen: The dictionary is probed with a binary search…

    So? We could have a drunk search a jumble of scrolls, but it might take a while. The question is only whether the word passes a “spell-check”. That’s Dembski’s rule. Either the word is in the dictionary or it is not. It doesn’t matter how we determine it, and it has nothing to do with the genetic algorithm for searching the sequence space. Theefficiency is measured by numbers of mutants, so the efficiency of the spell-checker is irrelevant.

    The question is whether we can successfully search the specified sequence space using a genetic algorithm—and we can.

    Quote

    GilDodgen: In the case of the Zachriel program a prescribed word in a prescribed location in a prescribed English dictionary, presorted to effect an efficient binary search, is conserved when a match is made.

    That is incorrect. A particular word is not prescribed. There is no singular goal. The English dictionary, on the other hand, is prescribed by Dembski’s own claim. That’s what we mean when we say “to form a word that will pass successfully through a spell checker”.

    Quote

    GilDodgen: Weasel and Zachriel are essentially identical concerning matching and conservation, but Zachriel requires more sophisticated programming techniques.

    Actually, the working aspects of the program are very minimal, about 30 lines of code.

    Quote

    GilDodgen: By the way, if you want to defeat Zachriel just enter a long random string containing only consonants.

    GilDodgen accidentally reveals an insight. The challenge is to “Start with a short 2 or 3-letter word…” But why does starting with a random sequence of consonants usually fail? For the same reason a “dictionary” of random sequences will fail. It is only because words in the English dictionary are related by history and by phonetic construction that an evolutionary algorithm works. “XXX” will never be found, nor will “XXX” lead stepwise to other words. Word Mutagentation belies Dembski’s notion that the search landscape of English words lacks “slopes”.

    Quote

    ‘MUTAGENATOR
    ‘for a random Word in population
    ‘Random for Mutation or Recombination
    ‘(reCombine set by form slider)
    If Rnd > reCombine / 100 Then

    ‘MUTATIONS
    ‘Random type of Mutation
    c = Random(1, 5)
    Select Case c
    Case 1 ‘Delete Mutation
    i = Random(0, lengthWord – 1)
    Mutation = Left(Word, i) & Right(Word, lengthWord – i – 1)
    Case 2 ‘Point Mutation
    i = Random(0, lengthWord – 1)
    j = Random(97, 122)
    Mutation = Left(Word, i) & Chr(j) & Right(Word, lengthWord – i – 1)
    Case 3 ‘Insert Mutation
    i = Random(0, lengthWord)
    j = Random(97, 122)
    Mutation = Left(Word, i) & Chr(j) & Right(Word, lengthWord – i)
    Case 4 ‘Remainders
    i = Random(1, lengthWord)
    j = Random(1, lengthWord – i + 1)
    Mutation = Left(Word, i – 1) & Right(Word, lengthWord – i – j + 1)
    Case 5 ‘Snippets
    i = Random(1, lengthWord)
    j = Random(1, lengthWord – i + 1)
    Mutation = Mid(Word, i, j)
    End Select

    Else

    ‘RECOMBINATIONS
    i = Random(1, lengthWord)
    j = Random(1, lengthWord – i + 1)
    Snippet = Mid(Word, i, j) ‘Take a snippet from Word

    == p = Random(loPop, hiPop) ‘Select another word from existing population
    Insert = Pop(p)
    lengthInsert = Len(Insert)
    q = Random(0, lengthInsert) ‘Pick a random point in this subject word
    Mutation = Left(Insert, q) & Snippet & Right(Insert, lengthInsert – q)

    End If

    call Validate(Mutation)

    ‘(Validate checks if Mutation is in Dictionary and not already in population.)

    Word Mutagenation does *not* even attempt to simulate biological evolution. It simply falsifies Dembski’s claim that genetic algorithms are “useless when searching to find a sequence of, say, 7 letters from a 26-letter alphabet to form a word that will pass successfully through a spell checker.” Dembski doesn’t know squat about evolutionary algorithms.

  15. But Dodgen has moved the goalposts – the author of the e-mail didn’t want ot simulate biological evolution – he wanted to show that RM+NS was an effective search strategy – which he did.

    Riiight…then why do Darwinists keep citing this website? Why not simply put a disclaimer up stating exactly that? Nope, the site says “This more closely approximates the process of biological evolution.” in reference to the Word Mutagenator program. If this Darwinist is correct about the emailer’s intentions I would not have a problem with them, since I clearly said in my last post: “It should be noted that such search methods are faster than a blind search.” But I still do not see the point of the emailer pointing out this program since the entire debate on UD is about biological evolution.

    Recently, Dembski has posted an unpublished draft paper on what he calls “Active Information”.

    Quote
    Dembski: Such assumptions, however, are useless when searching to find a sequence of, say, 7 letters from a 26-letter alphabet to form a word that will pass successfully through a spell checker… With no metric to determine nearness, the search landscape for such searches is binary—either success or failure. There are no sloped hills to climb.

    Incredibly, Dembski repeated Pitman’s debunked claim.
    …..
    Word Mutagenation does *not* even attempt to simulate biological evolution. It simply falsifies Dembski’s claim that genetic algorithms are “useless when searching to find a sequence of, say, 7 letters from a 26-letter alphabet to form a word that will pass successfully through a spell checker.” Dembski doesn’t know squat about evolutionary algorithms.

    The paper referred to:

    http://cayman.globat.com/~trad.....T/Hag2.pdf

    Apparently this Darwinist did not bother to read further:

    Active information is indispensable for increasing the probability of success of a search. Active information applied to a search should not be prescribed blindly, but must accurately reflect constraints on the target location. If in the search for “Ace of Clubs symbol” we are told that we are getting “warmer” when in fact we are getting “colder,” the active information contributed to the search can, depending on the algorithm crafted around this information, be negative and thus result in a probability of success less than that of random search. The NFLT presupposes the absence of active information.
    ….
    The prior assumptions” and problem specific knowledge” required for “better-than-chance performance” in evolutionary search derives from active information that, when properly fitted to the search algorithm, favorably guides the search.
    …..
    The NFLT shows that claims about one algorithm outperforming another can only be made in regard to benchmarks set by particular targets and particular search structures. Performance attributes and empirical performance comparisons cannot be extrapolated beyond such particulars. There is no all-purpose “magic bullet” search algorithm for all problems.
    ….
    Although commonly used evolutionary algorithms such as particle swarm optimization [9] and genetic algorithms [11] perform well on a wide spectrum of problems, there is no discrepancy between the successful experience of practitioners with such versatile algorithms and the NFLT imposed inability of the search algorithms themselves to create information [4, 10]. The additional information often lies in the experience of the programmer who prescribes how the external information is to be folded into the search algorithm. The NFLT takes issue with claims that one search procedure invariably performs better than another or that remarkable results are due to the search procedure alone

    It’s rather obvious when reading the rest of the paper that Dembski is using a random search as his baseline for his comment. This Darwinist is purposely quoting Dembski out of context to make it appear as if he is saying evolutionary algorithms are not capable. Either this Darwinist is lying or failed to read the entirety of the document. I’ll be nice and assume the latter. Now since this document is a draft it could be suggested that Bill could make this clearer within that one sentence. That way Darwinist do not get more confused.

    The Darwinist also states:

    It is only because words in the English dictionary are related by history and by phonetic construction that an evolutionary algorithm works.

    Zachriel’s evolutionary/genetic algorithms were constructed with active information to take such things into account. More active information could be used to take things like “XXX” into account. This entirely follows with what Dembski was actually saying in the article. Also, notice that in my previous post methods 4 and 5 also had active information but because I poorly designed the fitness function the results would thus be poor as well.

  16. GilDodgen used VBasic for development?

    Yes, plus much integrated C code. The mission planner’s guided airdrop algorithms are not computationally intensive, and VB profides many tools that make user-interface and wireless communications development easy.

    This is not hard: Simply print out the dictionary contained in the Zachriel program and be done with it. No search is necessary, because all the requisite information has been supplied by the programmer in advance.

  17. BarryA, “- he wanted to show that RM+NS was an effective search strategy – which he did.”

    Wrong. There’s not one “natural” thing about the “effective search strategy – which he did.”

    There is no evidence whatsoever that anything in natural systems behave the way Zech’s method acts.

  18. I had assumed the Nilsson and Pelger work was an actual computer program. Gil’s right, it’s not. I had their paper in my files all along and it’s a mathematical projection of the number of generations to produce a focused eye lens from a light-senstive patch. See Proceedings of the Royal Society of London, 1994 256, pp. 53-58

    However, even leaving aside the magnificently complex IC biochemical system that turns a photon into an electrical current in a “light-sensitive patch”, the Nilsson and Pelger study still illustrates a trial and error process to reach a predefined goal – a journey intelligently designed to scale a known Mount Improbable. That is not the Darwinian process.

    (As an aside, I too use Visual Basic for my development. In fact, I originally wrote my products in C, but translated them to VB because of the rich development environment and the many third party controls that are available. Part of what I write are simulation programs. See http://www.portagecommunications.com)

  19. Want to read something reallyfunny? On TalkOrigins CB301, Mark Issak writes that any objection to eye evolution falls under the argument from incredulity. I would state, rather, that his arguments fall under argumentum ad ignorantiam. Mark further states that Darwin had doubts (as we all know well), then rescinded them by listing proposed intermediate stages, then commenting that “

    All of these steps are known to be viable because all exist in animals living today. The increments between these steps are slight and may be broken down into even smaller increments. Natural selection should, under many circumstances, favor the increments. Since eyes do not fossilize well, we do not know that the development of the eye followed exactly that path, but we certainly cannot claim that no path exists.

    Go to:
    http://www.talkorigins.org/indexcc/CB/CB301.html

    Be sure to click on the Don Lindsay ‘Fish Eye’ link.

    “In fact, taxonomists say that eyes have evolved at least 40 different times, and and possibly as many as 65 times. There are 9 different optical principles that have been used in the design of eyes and all 9 are represented more than once in the animal kingdom. Why so many? Well, because there was time”.

    Link to the Nilsson Pelger paper (Jodkowscy’s Polish site is the only free one I’ve been able to find).
    http://www.jodkowski.pl/kk/DENilsson001.html

    Darwin’s nemesis is now the neoDarwinist’s nemesis.

  20. Someone wrote,

    In fact, taxonomists say that eyes have evolved at least 40 different times, and and possibly as many as 65 times.

    Eyes exist, and since only evolution can account for the existence of biological systems, the eyes must have evolved. Therefore there are obviously easy paths by which eyes can evolve. Evolution is evidence for evolution! 40 or even 65 times!

  21. Sorry if this has been addressed already, but… has there been a recent overview of programs-simulating-evolution, written from an evolution-skeptical or ID point of view?

    Especially, I would like to know, what simulations of RM+NS have been done that, in the author’s opinion, to show that the process *cannot* generate any new information of interest?

    I’m a programmer and would enjoy helping develop a simulation that fixes some of the deficiencies of existing ones that are skewed to demonstrate the power of evolution. But I realize it’s a complex field, in which I’m not a specialist, and so would probably better spend my time collaborating with somebody who knows more, than trying to do something on my own.

    On another topic, I think we need to be careful on both sides about saying “this simulation (or analogy) has nothing to do with evolution”. That’s an accusation that gets leveled at pro-ID arguments as often as it does at pro-evo arguments. When it gets thrown at us, the response is usually (and rightly) “Yes, there are limitations to the precision of the simulation. It was designed to demonstrate certain things, and not others.” My point is that we need to extend the same understanding to pro-Darwinian simulation attempts: recognizing what they are designed to show and what they are not; and not rejecting them wholesale (and mocking them) just because there are significant aspects of biological processes that they don’t model.
    Not long ago in email I mentioned to a Darwinist, Paley’s (?) analogy about shaking watch parts around in a box and hoping they formed a working watch. I acknowledged that it was a crude analogy and went on to talk about crude analogies. The Darwinist responded more or less “How do you think this resembles evolution? … if that is the best you can do, as far as I’m concerned you are a lost cause … so blinded by religion…” In other words, he assumed I was presenting the analogy as a full-fledged model of the evolutionary process — something I didn’t claim or intend. So he ended up trashing a straw man.

    We need to avoid making the symmetric mistake. It seems to me we need to take pro-evo simulations with a generous spirit, not mocking them for failing to accomplish certain goals that the author may not have intended or claimed, but simply pointing out in a respectful way what they do and don’t demonstrate. In this case, the author says “Word Mutagenation does *not* even attempt to simulate biological evolution. It simply falsifies Dembski’s claim that …” Leaving aside his misleading quotation of Dembski, it seems that criticism of Word Mutagenation for not resembling evolution needs to be tempered to an informational tone rather than a triumphant refutation of the author (which would be beating a straw man).

    Otherwise, Darwinists will see that we’re crowing over imagined victories, rather than leading by example in sticking to the evidence and seeking a way forward through continually-mutually-refined research.

    Don’t you agree?

  22. lars,

    I think you make some good points, but not without a little confusion. If you’re concerned about Darwinist bias in presenting evidence such as computer simulation, you shouldn’t counter that with something from an “ID point of view.” The proper way to argue against a biased point of view is to maintain objectivity. Fighting prejudice with prejudice is rarely very helpful.

  23. lars:
    “Eyes exist, and since only evolution can account for the existence of biological systems, the eyes must have evolved. Therefore there are obviously easy paths by which eyes can evolve. Evolution is evidence for evolution! 40 or even 65 times!”

    I’m not sure that anyone here disputes that. What is being discussed is whether eyes in reality (or in a simulation) evolve via a Darwinian mechanism or some other unknown mechanism.

    The criticism of the simulations is that they do not use a blind-to-the-future Darwinian approach. They are examples of front-loading: the goal is known at the outset. They are therefore examples of a form of evolution by intelligent design.

    If someone creates a simulation or projection of evolution that is based on intelligent design while claiming that it is an example of Darwinian evolution, then they are very likely going to be mocked.

  24. I don’t know about you guys, but I’m seeing all the preliminary evidence, for information conservation, line up with novel creation of parent species;

    I found this site on the eye:

    http://www.darwinismrefuted.co.....ty_05.html

    Of Special note:

    There are many different types of eye in the living world. We are accustomed to the camera-type eye found in vertebrates. This structure works on the principle of the refraction of light, which falls onto the lens and is focused on a point behind the lens inside the interior of the eye.

    However, the eyes possessed by other creatures work by very different methods. One example is the lobster. A lobster’s eye works on a principle of reflection, rather than that of refraction.

    The most outstanding characteristic of the lobster eye is its surface, which is composed of numerous squares. As shown in the picture, these squares are positioned most precisely. As one astronomer commented in Science: “The lobster is the most unrectangular animal I’ve ever seen. But under the microscope a lobster’s eye looks like perfect graph paper.”356

    These well-arranged squares are in fact the ends of tiny square tubes forming a structure resembling a honeycomb. At first glance, the honeycomb appears to be made up of hexagons, although these are actually the front faces of hexagonal prisms. In the lobster’s eye, there are the squares in place of hexagons.

    Even more intriguing is that the sides of each one of these square tubes are like mirrors that reflect the incoming light. This reflected light is focused onto the retina flawlessly. The sides of the tubes inside the eye are lodged at such perfect angles that they all focus onto a single point.

    The lobster eye is composed of numerous squares. These well-arranged squares are in fact the ends of tiny square tubes. The sides of each one of these square tubes are like mirrors that reflect the incoming light. This reflected light is focused onto the retina flawlessly. The sides of the tubes inside the eye are lodged at such perfect angles that they all focus onto a single point.

    The extraordinary nature of the design of this system is quite indisputable. All of these perfect square tubes have a layer that works just like a mirror. Furthermore, each one of these cells is sited by means of precise geometrical alignments, so that they all focus the light at a single point.

    Michael Land, a scientist and researcher at the University of Sussex in England, was the first to examine the lobster eye structure in detail. Land stated that the eye structure had a most surprising design.357

    It is obvious that the design in the lobster eye presents a great difficulty for the theory of evolution.

  25. Mike1962: Sorry for the confusion, but commenet 14 is not from me. It is a copy of an email I received from the other side. They can’t post directly, because they are banned here.

  26. StuartHarris:

    The criticism of the simulations is that they do not use a blind-to-the-future Darwinian approach. They are examples of front-loading: the goal is known at the outset.

    This is the key point. As I pointed out in my comment #16, no search is even necessary, because what is being sought was already found before the program was even launched. The algorithm simply represents a very awkward way of looking up words in a dictionary. It is no great accomplishment to find something that was never lost, and to do so very inefficiently.

  27. barrya, ok.

    btw, i didn’t mean to sound so blunt.

  28. Re Lee Bowman in 19:

    A little more on the eye:

    http://www.darwinismrefuted.co....._1_05.html

    The very first eye to suddenly appear in the fossil record was attached to one of the very first complex organism to abruptly appear in the fossil record: The now-extinct trilobites:

    “One of the most interesting of the many different species that suddenly emerged in the Cambrian Age is the now-extinct trilobites. Trilobites belonged to the Arthropoda phylum, and were very complicated creatures with hard shells, articulated bodies, and complex organs. The fossil record has made it possible to carry out very detailed studies of trilobites’ eyes. The trilobite eye is made up of hundreds of tiny facets, and each one of these contains two lens layers. This eye structure is a real wonder of design. David Raup, a professor of geology at Harvard, Rochester, and Chicago Universities, says, “the trilobites 450 million years ago used an optimal design which would require a well trained and imaginative optical engineer to develop today.”

    A 2001 Science article says:

    Cladistic analyses of arthropod phylogeny revealed that trilobites, like eucrustaceans, are fairly advanced “twigs” on the arthropod tree. But fossils of these alleged ancestral arthropods are lacking. …Even if evidence for an earlier origin is discovered, it remains a challenge to explain why so many animals should have increased in size and acquired shells within so short a time at the base of the Cambrian.”

    As well the Chinese Cambrian fossil field is said. by Dr. Paul Chien possesser the largest collection of Chinese Cambrian fossils in North America, to be excellent in its preservation of so^ft * bod^ ied fossils both before and during the Cambrian explosion.

    That pretty much destroys their “The eye evolved because there was time for it to evolve” argument doesn’t it.

  29. Mickey:

    If you’re concerned about Darwinist bias in presenting evidence such as computer simulation, you shouldn’t counter that with something from an “ID point of view.” The proper way to argue against a biased point of view is to maintain objectivity. Fighting prejudice with prejudice is rarely very helpful.

    I agree with you in principle, and maybe I didn’t express myself as clearly as I would have liked. Probably because my thinking is not fully resolved. Ideally one should be objective; but all sides are likely to claim objectivity, when in fact they’re not always objective. A lawyer for the defense may say “The prosecution is pro-guilty, but here is an objective analysis,” and bravo if it’s true, but a rational jurist will assume the defense has its own bias and try to evaluate the evidence he presents in that light. I know I would be perceived more as a defense lawyer than a jurist in this court case, and perhaps rightfully so.

    So it seems to me more helpful to state your prejudices, while doing your best to think and work objectively. That’s why I hesitate to say “let’s have an objective simulation rather than a Darwinly-biased one” even though that is what I would like to see.

  30. StuartHarris (#24),
    Probably what I said was confusing since in #20 I was mocking an evolutionary argument, and in #21 I said let’s not mock evolutionary simulations. Listen to what I say, not what I do. :-S (I didn’t mean the two to be connected.) However…

    If someone creates a simulation or projection of evolution that is based on intelligent design while claiming that it is an example of Darwinian evolution, then they are very likely going to be mocked.

    It may be likely, and possibly deserved, but it seems to me neither necessary nor helpful. If I were in their shoes (say I had put together a simulation that I felt supported ID, and some Darwinists found some actual weaknesses in it, or at least aspects it didn’t address), what response from them would be likely to yield progress in the debate — respectfully and generously pointing out the shortcomings, giving the benefit of the doubt; or mocking the whole thing as “yet more IDiocy” ? You get the point. The former would certainly win more respect from me, and more willingness to work together toward a simulation that many on both sides could agree was reliable and showed something significant about the capabilities of relevant processes.

  31. The question is whether we can successfully search the specified sequence space using a genetic algorithm—and we can.

    Right and the “genetic” algorithm was written by an intelligent angency.

    As for the evolution of the eyes/ vision system- no one can simulate that until we understand cellular differentiation and all the other aspects- what DNA sequence(s) are involved- required to construct the eye and vision system.

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