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Gil Has Never Grasped the Nature of a Simulation Model

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Tom English challenged me with this:

I say categorically, as someone who has worked in evolutionary computation for 15 years, that Gil does not understand what he is talking about. This is not to say that he is trying to mislead anyone. It is simply clear that he has never grasped the nature of a simulation model. His comments reflect the sort of concrete thinking I have tried to help many students grow beyond, often without success.

The reason for Tom’s lack of success is that he, and Darwinists in general, try to explain everything with an overly — indeed catastrophically — simplistic model. Here’s what’s involved in a real-world computer simulation:

My mathematical, computational, and engineering specialty is guided-airdrop technology. The results of my computer simulations, and their integration into the mechanics of smart parachutes, are now being used to resupply U.S. forces in Afghanistan. C-130 and C-17 aircraft can now drop payloads from up to 25,000 feet MSL, out of range of enemy small-arms, shoulder-launched missile, and RPG fire, and the payloads autonomously guide themselves to their targets within a CEP (circular error probable) of approximately 26 meters. Did I do all of this highly sophisticated mathematical and software simulation without ever having “grasped the nature of a simulation model”?

One small part of developing this technology involves mathematically and computationally simulating the descent rate of a parachute and its payload at various altitudes. This includes the following: the drag coefficient of the parachute, the chute reference area, the density of the air at various altitudes (not only determined by altitude but lapse rate — the rate at which air temperature changes with altitude), and other subtle considerations, such as the flow-field effects of the payload which changes the drag characteristics of the parachute.

If any mathematical, computational, or real-world assumptions about any of these factors are wrong, or if any unforeseen factors are left out (and what I described above represents a small percentage of what’s involved), the simulation breaks down. We do our best, but we never know for sure until we throw the thing out of an airplane, see where it lands, and tediously analyze the telemetry data recorded by the in-flight computer.

Based on these observations and computer simulations that can be tested in the real world, what confidence can anyone have that biological evolutionary computer simulations have anything to do with reality?

The answer is: none. It’s all fantasy and speculation, masquerading as science.

Comments
Tom English writes: There is considerable debate as to which salient features of biological evolution should be preserved in an abstract model of evolution. Gee, ya think? If you were actually modeling a biological system you could continually test your simulated results against the real world to see how close you were to having everything (or enough of everything) right. But because you're just wool-gathering you can't test your models. You can model pink unicorns if you want but until there's a pink unicorn to be found in the real world to see if they behave like your model that would be wool-gathering too.DaveScot
October 2, 2006
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Tom English It occurs to me that biological computer simulations would not exist without intelligent designers afoot. Does that prove that real biologic organisms too would not exist without an intelligent designer afoot? According to your fantasy=reality logic that must be true.DaveScot
October 2, 2006
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Ha Jason! I beat you to the punchline. I will concede that your laser-wielding super-humans beats my non-descript book of fairy tales. But you know what they say, the early bird catches the worm... :-)DaveScot
October 2, 2006
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Tom A computer can be designed without knowledge of a Turing machine. I have no idea what point you meant to make with that. Is it one of those sweeping statements like "nothing in biology makes sense except in the light of evolution" where only the hand waving pundits actually believe it? The bottom line remains that none of the digital organism programs I' ve seen are modeling anything in the real world which can be used to determine if the model is accurate.DaveScot
October 2, 2006
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I once created a picture in MS paint of 15 feet really buff humans carrying large laser fired weapons, battling off slimy green aliens. I wonder what city they're currently in. I wonder if they know me as their creator? Will it be legal to keep them as pets? Or will they have rights as any other person?JasonTheGreek
October 2, 2006
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A computer simulation IS not the same thing as a real world event in nature where a trillion accidental mutations occur that give rise to new information, systems, body types, etc. If the computation has successfully produced an IC system, it's automatically done it in the real world in biology? Hardly. We can't even predict hurricane paths or basic weather patterns correctly half the time, but whatever takes place in a GA simulation equals what has happened in the real world, even if real world (biologically speaking) time frame equals millions of years? Far fetched doesn't even begin to describe the scenario.JasonTheGreek
October 2, 2006
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Tom English An evolutionary computation is an evolutionary process in the real world. If the computation does something, an evolutionary process in the real world has done it. If you cannot grasp this, then you are not grasping what much of evolutionary computation is about. So by your logic a book of fairy tales are fairy tales in the real world. Ooooooooooooookay. Whatever you say.DaveScot
October 2, 2006
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Karl:
Avida has shown that a Darwinian process is capable of producing irreducible complexity.
Nonsensical statements like this will quickly get you unselected from this blog. And the ID proponents who post here, know better than to buy such claptrap. Consider this a warning.Scott
October 2, 2006
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JasonTheGreek:
Because a computer simulation purports to show something is possible doesn’t mean it’s possible or anywhere near possible in the real world. That should be noted first off.
An evolutionary computation is an evolutionary process in the real world. If the computation does something, an evolutionary process in the real world has done it. If you cannot grasp this, then you are not grasping what much of evolutionary computation is about.Tom English
October 2, 2006
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DaveScot:
The thing about abstraction, Tom, is that we can quickly take an abstract straight to absurdity.
Agreed. But what do Turing machines, production systems, and the lambda calculus have to do with electronic digital computers? How can it be that such abstract systems, none of which has a real implementation, serve as model computers in a hugely successful theory of computation? There is no notion of system failure in any of them, so some here must say, for consistency with their prior remarks, that the theory has nothing to do real computation. This is balderdash, of course. The object of study is computation, and a key issue is how the properties of the model computer limit the possible computations. Incidentally, I don't think Turing knew of the American implementation of an electronic digital computer when he conceived of his abstract computer. He was not modeling anyone's computer, but he came up with what has proved to be the most useful of all model computers. By useful, I mean that it appears in more theorems in the theory of computation than does any other model computer. Something to contemplate is the an electronic digital computer is not "really" a Turing machine. It is quite literally a finite state machine, but the number of states is so large that the Turing machine, with its infinite storage (something that cannot exist), is a more useful model. I mention this to emphasize that a "false" model is sometimes a better choice than a "true" one. Modeling is more about utility than reality. In evolutionary computation we explore in theory and in simulation the properties of abstract evolution. There is considerable debate as to which salient features of biological evolution should be preserved in an abstract model of evolution. But everyone in my community agrees that radical abstraction is as important to understanding of evolution as it has been to understanding of computation. I think many here are mistakenly assuming that we are out to model biological entities. In fact, our models are our objects of study, just as Alan Turing's abstract computer was his.
That’s why we make sure that models whose results can cause loss of life and property (say like tornado prediction) are limited as much as practical in the abstact and tested as much as is practical against the real world process being modeled.
The properties of computation are independent of the particulars of real-world computers. It makes just as much sense for us in evolutionary computation to seek abstract principles of evolution. ID theory is founded on the notion that information is central to life, so why is this such a radical concept?Tom English
October 2, 2006
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Avida is a joke.John A. Davison
October 2, 2006
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Karl Pfluger:
Avida has shown that a Darwinian process is capable of producing irreducible complexity.
Can you provide an example that is worth my perusing.? I've wasted much time being pointed by others in the direction of modeling examples that are clearly "sneaking in" information via fitness functions and such, so please give me an example, a model, that is worth investigating.PaV
October 2, 2006
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Recip Bill:
That said, your comment misses the point of my post, and Tom’s earlier lament. Selectionist causation exhibits substrate neutrality (e.g. is not limited to biological systems) independent of its origins.
In responding to Karl, above, I mentioned that Fred Hoyle likened the common understanding of evolution to a feedback loop with a selection coefficient. If we live in a world that is orderly, one cannot help but suppose that rather than persisting in chaos, nature is going to find some sort of solution. The selection coefficient will be either positive or negative, and probability of a certain physical state will either move to 1 or 0. The term selectionist causation sounds almost mystical. Why not just say: "We find nature involves feedback loops"? But, all of this points to "order". And the question becomes, Whence the order from chaos? Of course, Genesis has an answer. And even physics has a kind of answer; but that answer then leads somewhat inexorably to the "anthropic principle". What is staggering about the universe is that we can understand it. Didn't Einstein have something to say along those lines?PaV
October 2, 2006
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57. StephenA
However, I predict that the effects of RM & NS if accurately simulated (even if only in a rather abstract sense) will not produce new information.
It's easy to show that random mutation can produce useful "information". Let's say that I have a simple gene sequence (sequence A): ACGGAC. Let's say that I mutate it at position 4, so it looks like (sequence B): ACGCAC. Is this an information increase, decrease, or the same? If we say that random mutation can't produce new information, sequence A must contain equal or more information than sequence B ( A >= B ). Now, let's mutate sequence B and call the result sequence C. There are six positions, each of which can be changed to three other values (18 possible mutations). So, each of those mutations has a 1 in 18 chance of happening. One of those mutations will change position 4 back to "G". In other words, it will change sequence B back into sequence A. If we say that random mutation can't produce new information, then sequence B contains equal or more information than sequence C ( B >= C ). But, if sequence C is sequence A, then ( A >= B >= C and A = C ). Now let's say that A to B was actually a decrease in information. That means B to C MUST be an increase in information. Thus, I've shown in a mathematically rigourous way, that mutation CAN increase information. Now, what about those other 17 mutations? If those other 17 mutations are bad, and only 1 is good, then mutations will, on average, be bad. That's true. That's where natural selection comes in. Natural Selection works to preserve the good mutation (organisms with the good mutation produces more offspring), and organisms with the 17 bad mutations reproduce more slowly or die before producing any offspring. If this is a sexually reproducing organism, that one mutation can actually spread across the entire species, giving every organism of the species a useful sequence. So, yes, RM+NS can produce new information. 60. todd
Avida proved IC can arise without intelligent cause? So then, what caused Avida?
If you want to compare GAs to the real-world, you have to make a distiction between universe-ID and biological/gene-ID. The programmers act as universe-intelligent-designers in the case of Avida. The ID movement spends most of it's time arguing that biological entities cannot arise out of the low-level laws of the universe (Behe says IC requires intelligent design but other systems can evolve through NDE, Dembski says nothing at all can arise out of NDE). This idea can be called "biological-ID". Your argument "what caused Avida" is the equivalent of saying, "Sure, biological organisms can produce IC through NDE, but who made the laws of the universe and who made the atoms that living things are made out of?" That criticism doesn't affect our argument that NDE can create IC. Your comment is only relevant if we were arguing that the universe was not created (universe-ID).BC
October 2, 2006
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Todd, Both Avida and biological evolution are instances of Darwinian processes. In both, organisms are able to reproduce and pass their characteristics to their offspring. In both, random mutations arise which affect the organisms' ability to survive and produce offspring. In both, selection pressures favor some varieties and penalize others. You seem to be hung up on the fact that the 'universe' and the selection pressures are artificial in Avida. But that is irrelevant to the question of whether Avida implements a Darwinian process. Again, the only ingredients required for a Darwinian process are reproduction, heritable random variation, and selection. Avida has all of these. Avida has shown that a Darwinian process is capable of producing irreducible complexity. Does that prove that biological evolution can also do so? Of course not. But what it does do (and this is extremely significant) is to show that nothing about IC is inherently unreachable by a Darwinian process. If you want to argue that biological evolution cannot produce IC, you can no longer simply say "Of course evolution can't produce IC, because no mindless Darwinian process can ever produce IC." You have to come up with specific reasons why biological evolution, unlike Avida, cannot generate IC. As I said before, this renders IC fairly useless as a concept, because we're back to where we were before the concept of IC was introduced: we look at a structure and ask ourselves, "Could that have evolved?"Karl Pfluger
October 2, 2006
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Karl Pfluger Nylonase is by definition an enzyme, not an organism. The suffix ase means enzyme. Get it? probably not. We now have organisms capable of degrading all kinds of things like diesel fuel. Does that make them new species? No and do you know why? It is because that is a reversible state that is why. To Darwimps like yourself any change is an evolutionary change. Right? Wrong. No evolutionary change from speciation on up to the formation of any of the higher categories has ever been shown to be reversible. If it is reversible it is not evolution. Let me know the next time you hear of a reptile having ever evolved into an amphibian or a bird into a dinosaur. "A past evolution is undeniable, a present evolution undemonstrable." John A. DavisonJohn A. Davison
October 2, 2006
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Tom English wrote:
There are people working in computational chemistry (e.g., simulation of protein folding), but proteins are no more the right level of granularity for evolutionary simulation than are transistors the right level for microprocessor simulation. If you truly know anything about microprocessor simulation, you know what I am saying.
DaveScot responds:
Your ignorance is showing again. http://www.ac.uma.es/hpca10/tutorials.html
Dave, What makes you think Sunil Kakkar is talking about simulating a processor at the transistor level? I see nothing in the excerpt you quoted to suggest that. Could you point to a specific passage? I've done processor design myself, and I can assure you that we don't simulate a processor at the transistor level. It would take forever and consume ungodly amounts of memory. As Kakkar notes, it already takes huge server farms to simulate a microprocessor. Why would we make the problem worse by simulating at the transistor level? Even the gate level is rarely used. Instead, the bulk of the simulation happens at the behavioral level. Formal verification tools are used to prove that the gate-level netlist is logically equivalent to the behavioral code, making it unnecessary to do extensive gate-level simulations.Karl Pfluger
October 2, 2006
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Todd Of course it is rude. Do you really think you can reason with ideologues of whatever persuasion? I know better and so did Einstein - "Then there are the fanatical atheists whose intolerance is the same as that of the religious fanatics and it stems from the same source...They are creatures that can't hear the music of the spheres." and so did Winston Churchill - "A fanatic is one who can't change his mind and won't change the subject." and so did Thomas Henry Huxley - "Of all the senseless bable I have ever had the occasion to read, the demonstrations of these philosophers who undertake to tell us all about the nature of God would be the worst, if they were not surpassed by the still greater absurdities of the philosophers who try to prove that there is no God." All three of these comments are in complete accord with the Prescribed Evolutionary Hypothesis. We are each a victim of our "prescribed" fate. All these internet forums are little more than venues for the presentation of ones largely innate, "prescribed" convictions concerning the fundamental question - WAS there a purpose in the creation of the universe or not? I do not regard that as subject to any form of debate or discussion and I have nothing but pity for those who feel otherwise. It is a monumental waste of time, at least of my time. "Militants on either side of intractable social issues would surely welcome a silver-bullet, a gene altering chemical, that would bring about conversions in their opponents." William Wright, Born That Way, page 166 Well folks, I hate to tell you but such a cure is not on the horizon and in my opinion never will be. In the meantime, rudeness will just have to do at least as far as I am concerned. If that is unacceptable there is always bannishment. I've been there - done that. At this point in my life I couldn't care less. "The best offence is to be as offensive as possible." John A. Davison "Carry the battle to them. Don't let them bring it to you. Put them on the defensive. And don't ever apologize for anything." President Harry S. Truman Got that? Write that down! I love it so! "A past evolution is undeniable, a present evolution undemonstrable." John A. DavisonJohn A. Davison
October 2, 2006
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John Davison, That's it? No response regarding nylonase?Karl Pfluger
October 2, 2006
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PaV: "Well, here you are explaining, of course, that “intelligence” is found in nature. This is an ID argument. Thank you for making it for us." Of course, some (not I) do argue that an "intelligence" installed the algorithmic process of variation and selection in nature - then allowed the process to operate without further intervention. Advocates of Deistic evolution, of course - not popular around here, I gather. That would be the only sense in which the algorithmic process of variation and selection can be recruited to something like ID. That said, your comment misses the point of my post, and Tom's earlier lament. Selectionist causation exhibits substrate neutrality (e.g. is not limited to biological systems) independent of its origins. Dennett goes on to attribute two additional properties to algorithmic processes - mindlessness and reliability. The passage is worth a squint, whether or not you find it congenial.Reciprocating Bill
October 2, 2006
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PaV wrote, Here’s how I see it: if you love equations, you become a mathematician; if want to explore equations, you become a physicist; if you want to use equations to do something, you become an engineer. Does that pretty much size things up?
If you want to wrestle equations in a vat of Crisco what do you become? :Dtodd
October 2, 2006
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Dr D, Does name calling ever advance an argument? While both men have issued pompous prose, neither have been rude. Name calling is rude. It's hard to believe, isn't it? ;)todd
October 2, 2006
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Is there any difference between Tom and Karl? Aren't they both chance-worshipping Darwimps? Iti s hard to believe isn't it? Who is next? I love it so! "A past evolution is undeniable, a present evolution undemonstrable." John A. DavisonJohn A. Davison
October 2, 2006
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Dave, If Tom is a mathematician by training, and you, like me, an engineer, then he'll never understand our practical side, and we'll probably never understand the abstract side. Here's how I see it: if you love equations, you become a mathematician; if want to explore equations, you become a physicist; if you want to use equations to do something, you become an engineer. Does that pretty much size things up?PaV
October 2, 2006
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Tom English On the power of abstraction. Is it possible that you yourself are a simulated organism a la "The Matrix"? The thing about abstraction, Tom, is that we can quickly take an abstract straight to absurdity. That's why we make sure that models whose results can cause loss of life and property (say like tornado prediction) are limited as much as practical in the abstact and tested as much as is practical against the real world process being modeled.DaveScot
October 2, 2006
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Recip Bill:
Read Dennett’s discussion of algorithmic processes in “Darwin’s Dangerous Idea” (p. 50). He argues that, by the same token that the logic of long division can be hosted upon virtually any physical substrate (”The power of the procedure is due to its logical structure, not the causal powers of the materials used in the instantiation, just so long as those casual powers permit the prescribed steps to be followed exactly”)
Well, here you are explaining, of course, that "intelligence" is found in nature. This is an ID argument. Thank you for making it for us.PaV
October 2, 2006
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Karl wrote, You seem to be making Gil’s mistake. The process doing the modeling is not the same as the process being modeled. The fact that the former requires intelligent input in order to operate does not mean that the latter does.
I find your argument lacking because the parameters by which AVIDA operate essentially 'front load' evolution. The specific critiques of AVIDA I've read point this out in more detail. The hand of the investigators are all over the latter, for it is defined by the former! Therein lies the rub and the paradox you don't see. I remain unconvinced a programmed simulation (ahem) falsifies the ID IC argument, which is precisely what you are claiming. For if it can be demonstrated that IC systems can arise without intelligent guidance (stochastically), then a central critique of materialist evolution is off the table. While this wouldn't 'prove' stochastic evolution, it certainly supports the notion. AVIDA proves programmers can set up conditions in a simple non-real model universe and produce IC. That they set the conditions, the search fields and rules of this universe (then produce IC) is apparently of no consequence to you! Wow. From where I sit, your argument is what I'll generously call "a stretch"... :)todd
October 2, 2006
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Karl Pfluger:
He means that any scenario in which there is replication, heritable variation, and selection constitutes an example of Darwinian evolution, whether or not it involves living creatures.
Let me clue you in, Karl, a computer is not a biological organism. I hope you understand the distinction. If you don't, I can explain it in greater detail.
To model a particular chaotic process, it is not enough to simply create another chaotic process. You have to come up with a chaotic process whose behavior matches the behavior of the system you’re trying to model. The fact that Tom’s model was better than any existing model in predicting sunspot activity is a significant achievement.
And it only took him 20,000 models to find a combination that gave him good answers. As I said, this is "trial and error."
Perhaps you don’t understand that Tom is using the word “chaos” in its technical sense.
Whether he is referring to a mathematically "chaotic" system or not, the fact remains that the "design fit", the final output of the model, is "chaotic". ThusTom's further point that he didn't "frontload" anything is rendered meaningless.
Yes, but when a computer breaks down, any simulations running on it will cease to produce meaningful results.
Thanks for pointing out the obvious. I suspect you grew up, and perhaps still live, in Germany, because the only other person I've met who is similarly condescending grew up there.
Read Tom’s statement, paying careful attention to the word ‘if’:
I, of course, understand what the word "if" means, in case you're wondering about that, too. My question to you is, "Have you read Searching Large Spaces"? There is no "model" of evolution in there. It's an entirely mathematical development. That is the point--it's an analytical approach, not a simulation.
PaV asks:
And what does this say about the likelihood of random mutation being able to “find” the right solution to protein folding?
Nothing. They are entirely different problems. The Folding @ Home project is trying to explain why proteins fold as they do. Natural selection is merely “trying” to find proteins which enhance fitness. Natural selection has no knowledge of protein folding and makes no attempt to explain it. Karl, you seem to be missing the point that if the proteins don't fold properly, then biochemical function comes to an end. I hope you understand that. And, of course, NS can't act on something that is not biologically active. Hence, the massive amount of computer power required to search out the proper solution to folding is an undertaking that "random mutation and NS" would in some way have to deal with. It validates the ID argument that these search spaces are enormous, hence rendering RM+NS hopeless. (How many iterations [=generations] can a computer run per second? Quite a few, I imagine.)
I wrote: 3. They are not the same system. In an airdrop simulation, one of them (#2) is simulating the other (#1). 4. If you wanted to simulate the effects of hardware or software errors on an airdrop, you would introduce the errors into the model of #1. PaV asks: "This is exactly what Gil is proposing. don’t you see it?" Not at all.
What you are blithely ignoring is that in statement #4 you acknowledge the ability to simulate CPU errors occurring in the primary simulation(model #2 simply models errors in the CPU running model #1). Dave Scot has already pointed this out. But, of course, you're denying that Gil, or anyone else, can do that, as in this exchange: PaV:As to Gil’s proposal, don’t computers, in fact, break down? Karl:"Yes, but when a computer breaks down, any simulations running on it will cease to produce meaningful results. I wrote:
We use our intelligence to solve “hardware” problems; what do cells use?
Karl answers:
To the extent they are able, they use their inherited repair mechanisms to undo the damage. To the extent they are unable, they die or cease to function properly.
You seem to have missed the point, Karl. Yes, I'm fully aware of the repair mechanisms that cells have. But you see, Karl, the analogy is that those repair mechanisms mimic what we humans would do to get the "hardware" up and running; and we humans, for the most part, are "intelligent agents". So, the suggestion is that those repair mechanisms were intelligently designed to avoid, as you've stated, the computer from breaking down.PaV
October 2, 2006
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Recip We already know that trial and error can find solutions to problems. This is not something that needs testing in the abstract. Avida proves nothing we didn't know already. What we don't know is if trial and error can produce organic life in the real world. To figure this out we need to first have functioning model of biochemistry in order to understand the limits that constrain the natural process. Trial and error can produce any solution that is physically possible given enough time to search and evaluate the possibilities. It isn't a question of if it works, the question is how fast does it work when the substrate is biotic. Back when the universe was thought to be infinite and unchanging there was no question of rm+ns having the time to produce life since the amount of time was as a big a chunk of infinity as needs be. Now that we know the universe is finite in size, age, and changes over time there are some serious limitations that rm+ns must deal with. The probabilities that it must overcome in the real world to accomplish what we observe in life is the key to whether or not it's a plausible explanation. In order to figure that out we have to model biochemistry and the natural environment to see how fast and how many trials can be produced & evaluated, or indeed, if it is even physically possible in a real natural environment for organic polymers to reach the self-replicating point.DaveScot
October 2, 2006
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Sorry the above is meant for Tom, not Karl.todd
October 2, 2006
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