Uncommon Descent Serving The Intelligent Design Community

So Much For Random Searches

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There’s an article in Discover Magazine about how gamers have been able to solve a problem in HIV research in only three weeks (!) that had remained outside of researcher’s powerful computer tools for years.

This, until now, unsolvable problem gets solved because:

They used a wide range of strategies, they could pick the best places to begin, and they were better at long-term planning. Human intuition trumped mechanical number-crunching.

Oh,my! Teleology raises its ugly head!

But, now, let’s hear it for Intelligent Design. Here’s what intelligent agents were able to do within the search space of possible solutions:

. . . until now, scientists have only been able to discern the structure of the two halves together. They have spent more than ten years trying to solve structure of a single isolated half, without any success.

The Foldit players had no such problems. They came up with several answers, one of which was almost close to perfect. In a few days, Khatib had refined their solution to deduce the protein’s final structure, and he has already spotted features that could make attractive targets for new drugs.

Random search: 10 years + and No Success
Intelligent Agents: 3 weeks and Success.

Is there a lesson to be learned here Darwinist onlookers?

Comments
Wasn’t that the whole point behind James Shapiro’s new book? That the evolution we witness is nothing like the “smooth tree” Darwin fantasized about and legions have worshipped since?
It could be the point of his book, but it would be a weak assertion, because genomics is beginning to fill gaps. Take a look at the Koonin book that was offered free from Amazon. It isn't free anymore, but it was offered. The tree metaphor doesn't work for single-celled organisms, because they exchange genetic material.Petrushka
September 20, 2011
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Could you tell me, specifically, what you mean by "modern researchers who WITNESS genomes crossing gaps"? Meanwhile, I'll have a look at those papers.Elizabeth Liddle
September 20, 2011
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Elizabeth, I strongly suggest you first read the papers I referred you to and think them through before continuing to argue the existence of complexity gaps/islands of functionality in the space of system configurations. It is not my idea, I only accept it based on the work of others. I don't see anything in those papers that would contradict common sense in the way TOE does. Please read the papers before commenting any further.Eugene S
September 20, 2011
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Nor any other kind of search can except intelligent interference.Eugene S
September 20, 2011
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The Case Against a Darwinian Origin of Protein Folds
That's one of those interesting arguments invoking the problem of big numbers. Not only are the numbers big, but he argues that there are no shortcuts to designing proteins. Which implies that it is impossible for a "natural" designer to design proteins. Which is the argument I raised on the contest thread, and which was rejected. So either Douglas is right,and proteins cannot emerge and evolve naturally, and must all be specially created, or he is simply wrong about the landscape, and they can evolve. If they can't evolve, it is certainly not possible for humans or any finite entity to design them. Remember Axe's observation that there are no shortcuts. It's evolution or intervention. For every protein.Petrushka
September 20, 2011
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Can you tell me what you are talking about? Link?Elizabeth Liddle
September 20, 2011
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But what about modern researchers who WITNESS genomes crossing gaps? If it wasn't a random search, then what was it?uoflcard
September 20, 2011
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I don't "deny intelligence to exist at all". I don't know where on earth you got that from. And I agree that "neo-Darwinian mechanisms" (if I've understood correctly what you mean by that) cannot "far-sighted evolutionary steps". I don't think they do. I think they produce very near-sighted steps, and it's the near-sightedness of the steps that is one of the most important pieces of evidence for a near-sighted intelligent system rather than a far-sighted intelligent system. We, on the other hand, embody far-sighted intelligent systems, by virtue of our brains, which allow us to make "forward models" of the consequences of our actions, and select those actions that are most likely to achieve our distal goals. I would ask that you don't attribute to me positions I do not hold, and have never indicated that I hold. Not only do I not "deny intelligence to exist at all", intentional decision making is actually my research area. I'd scarcely study it if I didn't think it existed.Elizabeth Liddle
September 20, 2011
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Here's an interesting discussion. My guess is that functional proteins didn't originally evolve from randomization of large reading frames but from smaller fragments. Cordes, M.H.J., Burton, R.E., Walsh, N.P., McKnight, C.J. & Sauer, R.T. (2000) An Evolutionary Bridge to a New Protein Fold. Nature Structural Biology 7, 1129-1132. Davidson, A.R., Lumb, K.J. & Sauer, R.T. (1995) Cooperatively Folded Proteins in Random Sequence Libraries. Nature Structural Biology 2, 856-863. Davidson, A.R. and Sauer, R.T. (1994) Folded Proteins Occur Frequently in Libraries of Random Amino Acid Sequences. Proc. Natl. Acad. Sci. USA 91, 2146-2150.Starbuck
September 20, 2011
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I am not an expert, so correct me if I'm wrong, but I thought everyone had recognized that the "continuous search space" idea is simply false. Observed in the fossil record as well as present-day evolutionary leaps. Wasn't that the whole point behind James Shapiro's new book? That the evolution we witness is nothing like the "smooth tree" Darwin fantasized about and legions have worshipped since?uoflcard
September 20, 2011
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It absolutely is, Elizabeth. That is blatantly obvious. What is not blantantly obvious is how neo-Darwinian mechanisms cause complex, seemingly far-sighted evolutionary steps. Seeing that you deny intelligence to exist at all, even in humans (as your flabbergasting denial of it in this case demonstrates), it is not that surprising that you cite neo-Darwinian mechanisms as the cause. You are simplying inferring the best known cause. We are doing the same thing, except we believe intelligence to exist (as evidenced by almost every second of our existence)uoflcard
September 20, 2011
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Thanks :)Elizabeth Liddle
September 20, 2011
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It depends greatly how you define relatedness. If in terms of common ancestry, I strongly disagree for obvious information theoretic reasons (with which you just agreed above).
Well, no, I didn't agree! What I mean by "relatedness" is simply differing by no more than a few sequences. If you can show that organisms that once lived, or currently live, must differ by more than a few sequences in the genotype from its immediate ancestors, then yes, we have an island. But the challenge for those claiming islands is to show that those islands are real. I don't see that "information theoretic" principles tell us that those islands must exist. I'm not sure what you are saying here, in fact.
As far as NFL is concerned, the way I interprete it is that overall for optimisation problems, no winner algorithm exists performance-wise. This appears to be in disagreement with what you are saying about genotype/phenotype search spaces. The way I construe NFL is that it does not really matter on the whole as far as search performance is concerned, which algorithm to choose. To get some benefit you always have to pay: no magic tricks are possible, including spontaneous complexity leaps
between taxa. I'm not sure what you are saying here, either. What do you mean by "no winner algorithm exists, performance-wise?" The NFL theorem tells us that if a variant drawn at random from the total "variant space" is has the same probability of fitness as a variant drawn from a nearby space, then evolutionary algorithms won't "perform" (i.e. find the high-fitness variants) any better than random search, which is sort of obvious - if a fitness landscape consists of a sea of spikes, evolutionary search won't help. However, that's not the form the fitness functions "searched" by phenotypes actually takes. Most mutations make very little difference to the reproductive success of the phenotype, which means that the "reproductively successful" parts of phenotype space are clustered together, and the fitness landscape, far from being spiky, is very smooth. Not only that, but it's high dimensional, so there is a high probability that some reasonably high fitness part of the landscape will be nearby along some direction. So, sure, evolution would have to "pay" for "complexity leaps between taxa". So, if there are indeed "complexity leaps between taxa", evolutionary algorithms won't cross the gap. But that, as I understand it, is somewhat different from Dembski's NFL argument which seems to say that evolutionary processes don't work any better than random search even when the fitness landscape is smooth. In fact, we know they do (hence "micro" evolution). So what about these "leaps between taxa"? You say:
That there are complexity gaps between different taxa I think is clear enough. The world is decrete, not continuous as was assumed at the times of Darwin. The Darwinian rendering of life as something plastic does not hold any more on the macro scale and, yes, there are islands of functionality.
And this is exactly the point at issue. Good to have it stated clearly (because, as I said, the NFL and the UPB are irrelevant to the evolutionary argument which posits a fitness landscape in which neither apply). And this is why, IMO, Behe has the only decent ID argument - that there are indeed "islands" (Meyer, of course, argues that the earliest Darwinian-capable entity is also such an "island"). But in my view it is by no means "clear enough"! Indeed, it is the contention of all evolutionary biology that it there is are no "complexity gaps" and it was Darwin's thesis - indeed, it was his explanandum - seeing evidence, in taxonomy, of a tree, he sought to explain the tree, or, at least, saw that if there was a tree, self-replication with heritable variance in reproductive success was a viable explanation for biological variety and adaptation. So it all hangs on these "gaps" :) And the trouble with any argument based on the existence of "gaps" is that gaps can be filled, and indeed, frequently are. It is, literally, an argument from ignorance "we don't know how X got from A to B, therefore design". But it's important, IMO, to understand that that is what the argument is. "Evolutionists" aren't saying: "Oh, sure, random search could get across that gap" - they are saying "there are no gaps". We all agree that random search can't cross the gaps!Elizabeth Liddle
September 20, 2011
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no.4 links to the home page of the BioInstitute. It is better to use this link instead.Eugene S
September 20, 2011
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Hopefully, I haven't broken any links. In any case, you have bibliographic info. It is easy to get the full text versions off the web, it is open access. D. Axe (2004), Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds, Journal of Molecular Biology,Volume 341, Issue 5, 27 August 2004, Pages 1295-1315. D. Axe (2010a), The Case Against a Darwinian Origin of Protein Folds, Biocomplexity Journal D. Axe (2010b), The Limits of Complex Adaptation: An Analysis Based on a Simple Model of Structured Bacterial Populations. Biocomplexity Journal D. Axe (2011), Correcting four misconceptions about my 2004 article in Journal of Molecular Biology, Blog post, Biological Institute website. Eugene S
September 20, 2011
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Elizabeth, It depends greatly how you define relatedness. If in terms of common ancestry, I strongly disagree for obvious information theoretic reasons (with which you just agreed above). In this terms, there is no connected tree of life. If relatedness in understood functionally then yes, I agree. The latter type of relatedness, in my opinion, speaks out loud for commonality of purpose and of design ideas behind living things. As far as NFL is concerned, the way I interprete it is that overall for optimisation problems, no winner algorithm exists performance-wise. This appears to be in disagreement with what you are saying about genotype/phenotype search spaces. The way I construe NFL is that it does not really matter on the whole as far as search performance is concerned, which algorithm to choose. To get some benefit you always have to pay: no magic tricks are possible, including spontaneous complexity leaps between taxa. That there are complexity gaps between different taxa I think is clear enough. The world is decrete, not continuous as was assumed at the times of Darwin. The Darwinian rendering of life as something plastic does not hold any more on the macro scale and, yes, there are islands of functionality.Eugene S
September 20, 2011
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Link?Elizabeth Liddle
September 20, 2011
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Well, we simply don't (yet) know how the whole thing got started. Darwin didn't attempt to explain that - his theory only applies once you have self-replication with heritable variance in reproductive success. So that remains a problem, but it's an OOL problem, not an evolutionary problem, although the two do overlap to some extent, as to solve the OOL problem you have to push back the earliest, Darwinian-capable entity. However, once you have that minimal, Darwinian-capable entity, there is no reason that I can see to postulate any other disconnection, and genetics (developmental genetics in particular) seems to me to confirm the incremental relatedness of living things rather than disconfirm it. But clearly you disagree :)Elizabeth Liddle
September 20, 2011
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I am sorry to have supposed deliberate dismissal of opponents’ claims on your part. But certain things that have been said a number of times appear to be going unnoticed by you for some reason. Maybe it’s me not noticing your answers. Sorry.
No problem. I appreciate your graciousness.
What precludes macroevolution from happenning in practice is the amount of information that needs to be generated/injected into the system to make a leap feasible from one island of functionality to another. I do not agree with your claim that the search space is continuous.
OK, but in that case, that is the argument we need to be having, not an argument about NFL. NFL is irrelevant to the question of the nature of the search space, as it is about averages over all possible search spaces. And we agree, in the case of micro evolution, that we do not have to consider all possible search spaces.
It is not. There is simply no time in the history of the universe to make macroevolution plausible. Experimental findings I referred to prove my point.
There certainly would not be enough "time in the history of the universe" for living things to be found by random search. That is why the theory of evolution posits that the search space is continuous - or, in Darwin's metaphor, that life forms a huge family tree. This is what I find a bit frustrating about these discussions - people keep saying how improbable evolution is because it can't reach islands of functionality, as though "evolutionists" are proposing that it can. We aren't. We are saying that what it reaches, and has reached, aren't islands. Darwin's theory of evolution does assume one starting island, that of self-replication with heritable variance in reproductive success, but posits that from that point onwards everything is connected. So challenging the hypothesis of connectedness is a legitimate way of challenging evolution IMO. What are straw men are the ideas that "evolutionists" think that evolutionary processes are a "random search", i.e. obviously wrong because "random search" doesn't have time to work (which is true, but evolution is not a random search); or that evolutionary processes don't work any better than random search in phenotype space (they do, or we wouldn't observe "micro" evolution).Elizabeth Liddle
September 20, 2011
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BTW, as regards solution rarity vs. solution isolation of functional islands in the search space, Douglas Axe deals with it nicely on the webpage of his Biological Institute. He empirically proves that islands of functionality do exist on the protein level.Eugene S
September 20, 2011
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8.2.1.2.3 by Elizabeth Elizabeth, "It explores (this metaphorical language is hampering us I think) only adjacent sequences to ones that work." This is microevolution. I agree with this. The bigger question is how to get to those sequences that work, to start with. You are not addressing that question. Once you provide substantial evidence it can happen spontaneously, you will have dealt with it adequately. So far, you haven't, unfortunately.Eugene S
September 20, 2011
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8.2.1.2.1 by Elizabeth Liddle Elizabeth, I am sorry to have supposed deliberate dismissal of opponents' claims on your part. But certain things that have been said a number of times appear to be going unnoticed by you for some reason. Maybe it's me not noticing your answers. Sorry. What precludes macroevolution from happenning in practice is the amount of information that needs to be generated/injected into the system to make a leap feasible from one island of functionality to another. I do not agree with your claim that the search space is continuous. It is not. There is simply no time in the history of the universe to make macroevolution plausible. Experimental findings I referred to prove my point.Eugene S
September 20, 2011
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It is a common mistake to assume that we can extrapolate a function over singularities.
Please explain what you mean by this. I am not aware that I was doing so. And you seem to be missing my point. Evolution doesn't have to explore "all thinkable amino acid residue sequence" and, of course doesn't. It explores (this metaphorical language is hampering us I think) only adjacent sequences to ones that work. And ones that work tend to be next door, phenotypically, to ones that also work. Approaching the problem with combinatorics is misleading you, just as it has misled Dembski. You are missing the point about the adjacency of solutions in phenotype space, also my point that having lots of parameters makes brings more parts of search space adjacent to a population at any given time, not fewer, thereby increasing the probability that a viable move will be found. In a high dimensioned fitness landscape, viable parts of it are more connected, not less.Elizabeth Liddle
September 20, 2011
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Elizabeth, It is a common mistake to assume that we can extrapolate a function over singularities. You have been pointed many times towards the literature where these claims are substantially justified. Refer to papers by Douglas Axe for example. In a nutshell, consider the number of all thinkable amino acid residue sequences (for a protein domain it is 20^150, and it is a huge number indeed, I can assure you) and compare it with those sequences that bear any biological meaning. Axe finds out that the ratio of functionality to no functionality is 1 in every 10^74 sequences (for any functionality whatever), if I remember rightly. To compare, the number of atoms in the observable universe is 10^80. E.g. Behe points out that a retina tissue needs a complex set of protein-protein intercations to enable the necessary curvature alone, to say nothing of any other parameter. This is all horrendously complex. These difficulties only escalate as we go from protein to cell, to tissue, to body because the number of parameters grows. Combinatorially, it is not at all clear to me that this problem can be easily dismissed as one becoming close to trivial insolubility as the number of parameters grows. What if I say that it might be closer to the phase transition than to the trivially insoluble edge? In any case, it must be rigorously demonstrated that parameter tuning moves towards trivial insolubility. I don't see what makes you think we can easily assume this to be the case. We do not have the right for an a priori dismissal like that. All possibilities must be slavishly tried if we are talking about a blind search without intelligence.Eugene S
September 20, 2011
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Programming of Life - Biological Computers - Ch. 6 http://www.youtube.com/user/Programmingoflife#p/c/AFDF33F11E2FB840/5/hRooe6ehrPsbornagain77
September 20, 2011
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To me, the fact alone that biological systems do allow solutions with incredibly high numbers of parameters is itself a miracle.
Not a miracle at all, it's the very high numbers of parameters that makes solutions virtually inevitable - it means the fitness landscape is very high dimensioned, so there is a high probability that somewhere in adjacent space, along some dimension, there will be a "bridge" to somewhere useful. Again, that's because what is being explored is phenotype space not genotype space, and in phenotype space, variants are adjacent to each other.Elizabeth Liddle
September 20, 2011
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Please justify your claim that "this landscape...is only defined for tiny islands of functionality in the search space". The reason you think I "do not notice" (I'll draw a veil over your other alternative) the problem of "how you drive your system towards those islands" is that I'm not convinced that any islands are actually reached! They don't have to be (though they may exist - an extra pair of hands would be nice, but we are are extremely unlikely to get them - wings would be more probable). All that matters is that there is useful connected land in some direction (and the directions are extremely numerous). I think the diffulty is that people forget that while mutations randomly occur anywhere in genotype space (to be precise, because "random" can mean too many things - can occur anywhere in the genome with fairly equal probability), they don't occur randomly in phenotype space. A mutation is far more likely to result in a phenotype that is very similar to the parental phenotype than one that is very different. In other words, while the "genotype space" explored may be "rugged", that's not what matters, because natural selection occurs at the level of the phenotype, and in phenotype space, the fitness landscape is very smooth.Elizabeth Liddle
September 20, 2011
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No, I know it doesn't, Eugene. However, I was not making that extrapolation. What I was doing was saying that if Dembski's application of NFL theorem is correct, then microevolution shouldn't be possible either, yet clearly it is. So why should we think that Dembski's application of the theorem to biological evolution is correct? Explain why the NFL theorems don't apply to microevolution but apparently do apply to macroevolution.Elizabeth Liddle
September 20, 2011
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In addition to parameter tuning. I am working in the area of combinatorial optimisation. And I know from my own experience that the problem of parameter tuning is intractable. It quickly becomes really hard to tune the behaviour of a complex enough system as the number of parameters grows. And quite often there may be no feasible solutions. In other words, quite often even intelligent intervention on our part can't help it, to say nothing of a blind search, whether or not it is accompanied by the natural selection filter: the search space is too large. To me, the fact alone that biological systems do allow solutions with incredibly high numbers of parameters is itself a miracle.Eugene S
September 20, 2011
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"So we immediately have, in front of us, a fitness landscape that can be climbed faster by evolutionary processes than by random search." Not immediately. The precise picture is that this landscape is not everywhere defined. It is only defined for tiny islands of functionality in the search space. The bigger problem which you either superficially do not notice or unwilling to recognise (unfortunately, having seen your responses, I am afraid I must admit the latter to be the case) is how you drive your system towards those islands where microevolutionary adaptations are made possible. The search space is so enormously vast that within timespan bigger than that of the entire universe it is not possible to plausibly get any biologically feasible solutions without a priori intelligent fine-tuning of vital parameters. Imaging a pile of junk, will it ever become a computer without intelligent intervention? But in this case the probabilities are mucho-mucho higher than for life to emerge spontaneously...Eugene S
September 20, 2011
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