Computer Simulations and Darwinism

_{Gil Dodgen

October 1, 2011

Intelligent Design}

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Okay dudes, no more talk about my abandonment of atheism. Here’s some science and engineering talk.

I know something about computer simulations. In fact, I know a lot about them, and their limitations.

Search algorithms (and especially AI-related search algorithms) are a specialty of mine, as is combinatorial mathematics.

The branching factor (the average number of moves per side) in chess yields approximately 10^120 possible outcomes, but the number of legally achievable positions is approximately 10^80 — the estimated number of elementary particles (protons and neutrons) in the entire known universe. Compare this to the branching factor of nucleotide sequences in the DNA molecule. Do the math.

Finite element analysis (FEA) of nonlinear, transient, dynamic systems, with the use of the most sophisticated, powerful computer program ever devised for such purposes (LS-DYNA, originally conceived at Lawrence Livermore National Laboratory in the mid-1970s for the development of variable-yield nuclear weapons) is another of my computer-simulation specialties.

Dyna has been used heavily in the automotive industry for simulating car crashes, so that cars can be designed to produce the least damage to occupants.

In these simulations everything is precisely known and empirically quantified (the material properties of the components — modulus of elasticity, mass density, shear modulus, precisely calibrated failure modes, etc.).

In addition, the explicit FEA time step (the minimal integration time step determined by the software based on the speed on sound in the smallest finite element and its mass density, which is required to avoid numerical instability) is critical. In my simulations the time step is approximately a ten-millionth of second, during which partial differential equations, based on the laws of physics (F=ma in particular) are solved to compute the physical distortion of the system and the propagation of the forces throughout the system in question.

One learns very quickly with FEA simulations that even with all of this knowledge and sophistication one must empirically justify the results of the simulation incrementally by comparing the results with the reality it attempts to simulate.

One false assumption about a material property or any of the other aspects of a simulation can completely invalidate it. Worse yet, it can produce results that seem reasonable, but are completely wrong.

So, the next time someone tries to convince you that a computer simulation has validated the creative power of the Darwinian mechanism of random errors filtered by natural selection in biology, you should tell them to go back to school and learn something about legitimate computer simulations, and how difficult it is to produce reliable results, even when the details are well known.

Comments

Elizabeth, I'm just jumping in at random, but this simply isn't so:
Natural selection is most certainly a “meaningful principle” and a very straightforward one, which is that heritable variation in reproductive success will lead to adaptation.
Natural selection is the selection of individual variations. The concept of natural selection does not include adaptation. You could argue that an individually selected variation is an adaptation, but above you distinguished the two by stating that one leads to the other. Is every inherited variation a selected one? Can a variation be inherited but not selected? It seems that in order to know the difference one would have to determine that a single variation was directly responsible for differential reproduction. How does one do that?
ScottAndrews_{October 3, 2011
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But Gil, the range of "existing" information in any given population that is "mixed and matched" is itself the result of mutations! Mutations - novel sequences - are constantly being drip-fed into the population, while others, including those least advantageous in the current environment, constantly leaking out. Why shouldn't this produce a continously operating homeostatic system that constantly optimises the population as the environment changes, and maintains it at an optimum when it stays the same? Especially as we know from simulations that this is exactly what happens!Elizabeth Liddle_{October 3, 2011
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Natural selection is most certainly a "meaningful principle" and a very straightforward one, which is that heritable variation in reproductive success will lead to adaptation. For it to happen, you have to have some mechanism for producting heritable changes in phenotypic characteristics that will affect an organism's probability of reproduction, and we know what this mechanism is - slight variations in DNA sequences as they are transmitted from one generation to the next. And no, they don't "do much of significance" usually, at least alone, or for the organism in which they appear de novo. Which is why they tend to just drift, or not, through the population, those that do enriching the pool of variance from which, as we know from direct observation, "nature" "selects" those variants that do turn out to be useful when the environment changes.Elizabeth Liddle_{October 3, 2011
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Natural selection (to the extent it is even a meaningful principle) does not operate to create new systems. All it does is apply a label to the fact that some creatures died out before their characteristics got fixed in the population, while their more fortunate siblings survived. The "creative" part of Darwinism is just random, slight, successive variations. Then there is the growing realization that random mutations might not do much of significance anyway . . .Eric Anderson_{October 3, 2011
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"But this is not what Darwinism ultimately claims. It claims that random errors ... can explain all of biology, including the evolution of a primordial single cell into the mind of Mozart." No. You left out natural selection. All that the random mutations do is produce the raw material that gets filtered out by natural selection. It isn't a straight-line path that says one radom mutation will propagat all the way. What happens is that many organisms will be generated, with many different random mutations, from which nature will select.Grunty_{October 3, 2011
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Eric, This entire discussion elucidates the essential difference between the ID inference to the best explanation (design) and Darwinian materialistic philosophy, which is hopelessly mired in the ignorance of the 19th century. Randomness is universally, progressively, and inexorably destructive. It always eventually degrades, and never ultimately produces, except in the pathological circumstances Behe has identified, and even there, randomness does destroy, although with a temporary survival advantage. As I mentioned, the notion that random errors -- of whatever variety, and whether or not filtered by natural selection -- can produce something like the following from a primordial single cell http://www.youtube.com/watch?v=UEQbgJ2J9D4 should be considered by any logical person to be preposterous on its face. This is snake-oil salesmanship of the highest order. (My apologies to snake-oil salesmen, since snake oil might actually have some beneficial properties.)GilDodgen_{October 2, 2011
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Thank you. The [what Avida paper?] answer I'd hoped for was "The evolutionary origin of complex features" Regardless, your quote above from that paper enabled me to find it.Charles_{October 2, 2011
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I discuss it in passing in my paper Gil linked to below. The specific sentence arises in the discussion portion of their paper, in the same breath where they attempt to wave off the obvious circularity problem in their arguments. They state: "Some readers might suggest that we ‘stacked the deck’ by studying the evolution of a complex feature that could be built on simpler functions that were also useful. However, that is precisely what evolutionary theory requires, and indeed, our experiments showed that the complex feature never evolved when simpler functions were not rewarded." It is the last phrase that is particularly telling, and demonstrates that the entire Avida exercise they undertook is a question-begging circular argument. The fact that the complex feature never evolved unless the program was systematically nudged toward the end target is, in my view, the real lesson of the Avida exercise. Namely, that complex features are not likely to arise without some kind of forward-looking target in mind. This coincides nicely with Behe's concept of irreducible complexity, as further elucidated in his later book "The Edge of Evolution" where he looks at just how much (or little) variation plus selection is actually able to accomplish. Undertsood properly, without Darwinian blinders on, the Avida results actually support Behe, rather than being a refutation of Behe, as they were intended.Eric Anderson_{October 2, 2011
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Eric, You wrote a superb essay deconstructing Avida. UD readers might like to check it out here: http://www.iscid.org/papers/Anderson_BitByte_020305.pdf I particularly enjoyed this paragraph:
What is more astonishing, is that the authors are aware of their circular reasoning, but blithely dismiss it. In the final discussion section, they state, “Some readers might suggest that we ‘stacked the deck’ by studying the evolution of a complex feature that could be built on simpler functions that were also useful. However, that is precisely what evolutionary theory requires . . .” Say what?? In other words, we have adopted as our premise the very conclusion we are trying to reach. In a particularly Darwinian display of twisted logic, the researchers seem oblivious to the fact that this circular reasoning invalidates their entire conclusion, and cheerfully waive it aside as an inconsequential technicality. At best such an approach manifests questionable judgment, at worst, self-deception.
GilDodgen_{October 2, 2011
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Indeed, there is a sentence in the Avida paper that is extremely telling To what Avida paper do you refer, please? A title or a link would be most helpful.Charles_{October 2, 2011
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...random variation followed by natural selection... An important distinction needs to be made here. The mixing and matching of existing biological information can produce substantially different outcomes, within the limits of that information. Any parent with two or more children can tell you that. But this is not what Darwinism ultimately claims. It claims that random errors (whether point mutations or other stochastic events, which flow endlessly from the fertile imaginations of Darwinists) can explain all of biology, including the evolution of a primordial single cell into the mind of Mozart. This is an extraordinary claim, which should require extraordinary evidence, not speculation and silly computer programs like Avida.GilDodgen_{October 1, 2011
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...what particular simulation of the Darwinian mechanism are you criticizing? All of them, insofar as they have any relevance to biological reality. The point is that computer simulations of the Darwinian mechanism in biology are completely irrelevant. They are completely detached from the reality they attempt to simulate, and are based on so many unverified assumptions that they should not be taken seriously by anyone with any legitimate scientific integrity. The only empirical evidence we have for the creative power of the Darwinian mechanism of random errors in biology has been elucidated by Michael Behe, and that is the partial destruction of existing systems to provide a survival advantage in a pathological environment. The extrapolation of this phenomenon to explain the origin of complex information-processing machinery should be rejected as superbly illogical and completely unwarranted on any legitimate scientific grounds.GilDodgen_{October 1, 2011
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NormO, I'm not sure I'd tell them to go back to school in a particular case. But we certainly could tell them to go back and look at the program again, carefully this time, to see if they can tell (from a programming standpoint, not a Darwinian wishful thinking standpoint) at precisely what point the particular specified information was first put into the program. The results will be telling.Eric Anderson_{October 1, 2011
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Gil, you make some valuable points about the need for precise, quantifiable, calculable inputs in order for simulations to produce useful results that match real-world situations. As far as organismal evolution, we aren't even close to being able to put a handle on what is going on biologically, and certainly can't program a reliable simulation at this stage. I happen to have been reading one of Bill Dembski's old essays today and was reminded of another fact that is, in my humble opinion, more central to the problem of many evolutionary algorithms. Specifically, whenever there is a target (whether Dawkins' "methinks it is like a weasel" or more recent efforts such as ev and Avida), anything within the programming that nudges the program to converge on the target, necessarily and by definition, increases the probability -- often to something nearing 1. By definition, this increased probability means that there is less contingency in the outcome, and, therefore, less complexity in any specification. These kinds of evolutionary algorithms give the appearance of being complex, but they in fact are largely deterministic. As a result, they simply cannot, as a matter of principle, produce complex specified information. Indeed, there is a sentence in the Avida paper that is extremely telling, which I view as the primary lesson behind Avida but which Darwinian proponents like to overlook. It is an acknowledgement that when they didn't carefully nudge the program in the right direction, it couldn't seem to get there on its own. And then there's the whole issue of the no free lunch algorithms, which, as I understand it, were specifically proposed in the context of evolutionary-type computer simulations to help properly recognize the conservation of information and avoid inadvertently attributing "new" information to the simulation when it in fact was programmed in at the beginning.Eric Anderson_{October 1, 2011
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Well this is all great Gil but what particular simulation of the Darwinian mechanism are you criticizing? I mean, if someone tries to convince me that a computer simulation has validated the creative power of the Darwinian mechanism of random variation followed by natural selection, should I just tell them to go back to school, or should I actually address the the particular weaknesses in their specific simulation? In other words, what the heck is the point of this post?NormO_{October 1, 2011
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