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Writing Computer Programs by Random Mutation and Natural Selection

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The first computer program every student writes is called a “Hello World” program. It is a simple program that prints “Hello World!” on the screen when executed. In the course of writing this bit of code one learns about using the text editor, and compiling, linking and executing a program in a given programming environment.

Here’s a Hello World program in the C programming language:


#include <stdio.h>

int main(void)
{
printf(“Hello World!\n”);
return(0);
}

This program includes 66 non-white-space text characters. The C language uses almost every character on the keyboard, but to be generous in my calculations I’ll only assume that we need the 26 lower-case alpha characters. How many 66-character combinations are there? The answer is 26 raised to the 66th power, or 26^66. That’s roughly 2.4 x 10^93 (10^93 is 1 followed by 93 zeros).

To get a feel for this number, it is estimated that there are about 10^80 subatomic particles in the known universe, so there are as many 66-character combinations in our example as there are subatomic particles in 10 trillion universes. There are about 4 x 10^17 seconds in the history of the universe, assuming that the universe is 13 billion years old.

What is the probability of arriving at our Hello World program by random mutation and natural selection? How many simpler precursors are functional, what gaps must be crossed to arrive at those islands of function, and how many simultaneous random changes must be made to cross those gaps? How many random variants of these 66 characters will compile? How many will link and execute at all, or execute without fatal errors? Assuming that our program has already been written, what is the chance of evolving it into another, more complex program that will compile, link, execute and produce meaningful output?

I can’t answer these questions, but this example should give you a feel for the unfathomable probabilistic hurdles that must be overcome to produce the simplest of all computer programs by Darwinian mechanisms.

Now one might ask, What is the chance of producing, by random mutation and natural selection, the digital computer program that is the DNA molecule, not to mention the protein synthesis machinery and information-processing mechanism, all of which is mutually interdependent for function and survival?

The only thing that baffles me is the fact that Darwinists are baffled by the fact that most people don’t buy their blind-watchmaker storytelling.

Comments
Figure 1DaveScot
June 11, 2006
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Gil, Your "Hello World" program's existence is even more wildly improbable to arrive at by chance and selection than you have stated. It is written in C. This presumes some BNR definition of the C language to begin with. How did that come about by chance and selection? It assumes a compiler written in some other language that can compile and interpret the C code. How did that come about by chance and selection? The compiler runs on an complex specified operating system, which runs on complex hardware which is composed of metallurgical, mineral, and plastic complexities that ..... well you get the picture. Multiply the probability of a "Hello World" program by the probability of the pyramid below it and you can come close to the un-stateable improbability of the world your program is trying to greet. Stu Harris www.theidbookstore.comStuartHarris
June 11, 2006
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And don't forget to put a couple rounds from a Glock nine through the motherboard once in a while to simulate meteor strikes that cause global extinctions. :lol: I kill me sometimes.DaveScot
June 11, 2006
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This is all so incredibly naive. All these programs have fitness functions which is explicitely a direction given by an intelligent agent. Nature has no fitness function. Nature, or rather Darwin's version of nature, doesn't give a flying flop if anything is alive or not. In fact any student of nature knows that the rule is utter sterility. Everywhere we look other than the thin skin of the planet earth is a completely sterile environment and nature is as happy as a clam with nothing alive. So get rid of all fitness evaluations in these so-called simulations of evolution and see what happens. :roll: -ds DaveScot
June 11, 2006
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2 Simple questions: 1. Does running this generator ALWAYS result in a program which displays Hello World? Which leads to... 2. If it truly is based upon the principles of RM+NS why couldn't it generate a program that displays a large variety of pithy comments including "I AM DAVESCOT/GOD! FEAR ME PUNY HUMAN!"? (And if the program ever did display that I'd start begging Dave not to do anything naughty while hacking my PC. ;) ) I'd really like to see the source code for this Hello World program generator. If it's anything like the “Methinks it is like a weasel” program then I propose a simple "survivability check". If after an iteration the resulting program fails to compile and execute then the variations that were "favored" don't survive to the next iteration. Oh, what's that you say? The generator no longer produces anything you say? Reality sucks, don't it.Patrick
June 11, 2006
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Raevmo: "What about Conway's game of life?" Conway's Game of Life is law-based:
What mathematicians call functions, and what scientists prefer to call laws cannot explain the origin of CSI. The problem is that laws are deterministic and thus cannot yield contingency, without which there can be no information. The problem with laws is that they invariably yield only a single live possibility. Take a computer algorithm that performs addition. Let us say the algorithm has a correctness proof so that it performs additions correctly. Given the input data 2 + 2, can the algorithm output anything but 4? Computer programs are wholly deterministic. They allow for no contingency and thus can generate no information. At best, therefore, laws shift information around, or lose it, as when data gets compressed. What laws cannot do is produce contingency; and without contingency they cannot generate information, to say nothing of complex specified information. -- William A. Dembski, Intelligent Design,. p. 165.
Given arbitrary starting patterns, Conway's Game of Life just creates pretty patterns. [Interestingly, it's possible to use it as a universal Turing machine, but that requires intelligent design:
von Neumann...had realized -- and proved -- that a universal Turing machine (a Turing machine that can compute any computable function at all) could in principle be "built" in a two-dimensional world. Conway and his students also set out to confirm this with their own exercise in two-dimensional engineering. It was far from easy, but they showed how they could "build" a working computer out of simpler Life forms. Glider streams can provide the input-output "tape," for instance, and the tape reader can be some huge assembly of eaters, gliders, and other bits and pieces. What does this machine look like? Poundstone calculates that the whole construction would be on the order of 10^13 cells or pixels. Displaying a 10^13 pixel pattern would rerquire a video screen about 3 million pixels across at least. -- Daniel C. Dennett, Darwin's Dangerous Idea]
j
June 11, 2006
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apollo230: "Gil, Panda's Thumb has responded to you with their own thread:" I am pleased that the Panda's Thumb crowd has created a thread designed to refute my arguments. This is indicative of the fact that a very sensitive nerve has been stricken, and that they are in a state of desperation to defend the indefensible.GilDodgen
June 11, 2006
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Raevmo: "What about Conway's game of life? There is no externaly imposed “fitness function”, just a few very simple rules that govern the interaction between neighboring cells. Yet I believe it has been shown that there are configurarions that increase in complexity forever." The same might be said of the Mandelbrot set, or the spread of frost across a window. The complexity seems to increase without limit, but in fact it is a mirage. These are all contingent situations, the game of life proceeds from a few simple rules and the initial conditions, and the results never differ, given the same starting point. There is never an increase in useful (specified) information. The crystal gets larger, but nothing truly informative ever occurs. Novelty without function is noise. The set of truly functional novel situations is so small in comparison with the total possible number of situations that they will never occur, which is the point of the original post.SCheesman
June 11, 2006
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"The basic idea is to start with a simple configuration of counters (organisms), one to a cell, then observe how it changes as you apply Conway's "genetic laws" for births, deaths, and survivals. Conway chose his rules carefully, after a long period of experimentation, to meet three desiderata: There should be no initial pattern for which there is a simple proof that the population can grow without limit. There should be initial patterns that apparently do grow without limit. There should be simple initial patterns that grow and change for a considerable period of time before coming to end in three possible ways: fading away completely (from overcrowding or becoming too sparse), settling into a stable configuration that remains unchanged thereafter, or entering an oscillating phase in which they repeat an endless cycle of two or more periods." http://www.ibiblio.org/lifepatterns/october1970.html It seems Conway's Life game was intelligently designed to produce interesting results. It is a type of front loading within the laws of nature. This may be one way the Intelligent Designer id it. Are we saying that Conway was not an intelligent designer?idnet.com.au
June 11, 2006
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A gentleman named RBH has posted the following on a Panda's Thumb thread mounted to respond to Gil's original post:

http://www.pandasthumb.org/archives/2006/06/evolution_of_co_2.html.

My personal critiques of his statements are in parentheses:

RBH:
“Discussions of computer models of evolutionary processes typically dissolve into confusion due to the failure to carefully distinguish between two kinds of models that differ in the information used to calculate fitness.

1. Models with global fitness calculations. These are Dawkinsian METHINKSITISLIKEAWEASEL sorts of models, where the fitness of a replicator is calculated as the distance of its phenotype from some target phenotype. The fitness equation “knows” the target state, and replicators are more or less fit (and therefore survive to replicate and/or recombine) based on relative similarity (e.g. the Hamming distance) to that target state. These kinds of models are not models of biological evolution, and claims that they are such models flatly misconstrue biological evolution. However, they are useful in demonstrating the power of cumulative selection, which is all Dawkins sought to do with his METHINKS illustration. He explicitly said that the METHINKS program was not a model of evolution, but only of cumulative selection and its power to transform tiny probability into high probability. Creationist have consistently and persistently misconstrued that program since it was published, and Dodgen's post is yet another example of that misconstrual.”

(the Dawkins algorithm aims to converge a random string of 26 letters to the target phrase METHINKSITISLIKEAWEASEL in a series of trials. It does so quite rapidly because each trial is compared to the target phrase and the matching letters are retained for the next round. Since when do Darwinistic processes have targets?

Additionally, RBH claims that these algorithms are not models of biological evolution but “only of cumulative selection and its power to transform tiny probability into high probability”. One of Darwinian theory's fundamental claims is that undirected biological evolution has the power to climb such “Mount Improbables” (Dawkins' phrase). All RBH has done really is to change the spelling of “biological evolution” to “cumulative selection” in his phrasing - apollo230)

RBH:
“2. Models with local fitness calculations. These are models in which the algorithm does not “know” what a target phenotypic state might be, but “knows” only what is better or worse in the local environment, where “local environment” means the values of relevant environmental variables in the volume of phenotype space actually occupied by the current population. The fitness equation of the algorithm can calculate relative fitness among the replicators in the population, based on some defined properties of the replicators in that environment. Most GAs are of this nature. If I want to evolve a population of artificial stock traders, I cannot write down the specific target phenotype — if I could, I wouldn't bother to use a GA, I'd just write it down and trade on it. However, I know some properties a good artificial trader should have, and I can write a fitness function that tests for values of those properties. For example, I might use risk-adjusted return over some historical data as the relevant property. All members of the population paper trade over that period, and the algorithm calculates each artificial trader's risk-adjusted return and ranks the traders on that measure to determine which survive to replicate, their probability of entering into recombination, and so on. The algorithm “knows” a property of artificial traders — relative risk-adjusted return, where better traders are higher — but “knows” neither what an excellent trader's phenotype would look like nor what the global maximum risk-adjusted return might be. It “knows” only how risk-adjusted return differs among the members of the current population.”

(here the claim is that the trader's phenotype would not be the target of the proposed algorithm, but rather the set of properties that would comprise a good trader. Seems to me that in algorithm-land, there is no real distinction between the ideal trader and the properties of such a creature. These targets are effectively identical (correct me if I am wrong. And again, there is a defined target-not allowed under Darwinistic rules. - apollo230)

RBH:
“Biological evolution is an algorithm of the second sort. The algorithm does not “know” a target phenotype in order to determine fitness on the basis of similarity to that target phenotype. Rather, the algorithm of biological evolution “knows” only locally determined fitness, where fitness is “calculated” implicitly as survival and relative reproductive success of the actual replicators in the population in a specific environment composed of physical variables and biological variables (conspecifics and other species).
As a consequence, any algorithm that incorporates a fitness calculation that refers to some phenotype (or genotype) not currently in the population is not a model of biological evolution. Biological evolution “knows” what's better or worse in the current population only by virtue of the differential survival and reproduction of the members of that population; it does not “know” an optimal phenotype or genotype toward which it should evolve.”

(the “locally determined fitness” is itself a target, and these algorithms are made to conveniently converge onto these destinations through “strictly random processes” -never mind the computer code that (behind the figurative curtain) converges the process to the target.

Another fundamental flaw here is that to simulate actual biological evolution one must use actual genetic systems and actual creatures. This notion that flesh-and-blood animals can be reduced to computer code and still be called creatures is to effectively confuse virtual reality with the authentic biosphere.

The Darwinists have used carefully designed computer games to declare victory for RM/NS on some tiny little speck - a microchip. Then, through mental sleight-of-hand, they expand this dwarfish province into a grand macrocosm called Earth. - apollo230)

Then, through mental sleight-of-hand, they expand this dwarfish province into a grand macrocosm called Earth.

Well sure. And why shouldn't they? These are the same guys that extrapolate the mechanism that causes finch beaks to enlarge or moth wings to darken into a mechanism able to cause bacteria to become baboons. If you're willing to make that leap of the imagination there's not many leaps you won't make. I think Dawkins may be in hot water for copyright infringement. METHINKSITISLIKEAWEASEL is ripped off from the game show "Wheel of Fortune". -ds

apollo230
June 11, 2006
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VCfRSN: "ll tht ws skd ws tht th cmptr prgrm crt th Hll Wrld prgrm thrgh RM + NS. Th prgrm ds XCTLY ths." ctlly, t mst hv sd tmtd rtfcl slctn, nt ntrl slctn. :lol: —————— Mark Frank: "Natural selection requires that each step be functional but it does *not* require it to be step towards a predetermined goal. That's the whole point." Exactly. And when there's no predetermined goal, complex specified information isn't generated.j
June 11, 2006
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What about Conway's game of life? There is no externaly imposed "fitness function", just a few very simple rules that govern the interaction between neighboring cells. Yet I believe it has been shown that there are configurarions that increase in complexity forever. Besides the game of life, there are plenty of simulations without external fitness functions that show how genetic information increases over time, the only external input being a random number generator, and without any predefined goals. In other words, there is no doubt that RM+NS *can* create novelty. Why is this so hard to accept? I thought ID had no problem accepting "microevolution", where organisms can be modified slightly and adapt to their environment. If you accept that, then you have to accept that genomes can increase in complexity. Adaptation means that the genome incorporates information about the environment, almost by definition. If a genome in that sense copiesinformation from the environment, it couldbe argued there is not net increase in information in the system as a whole. So conservation of information, everybody happy.Raevmo
June 11, 2006
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Darwinists are not able (or willing) to recognize design either in nature or in their algorithms.apollo230
June 11, 2006
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Avida, Weasel and other simulations are desperate attempts of Darwinists to prove evolutionary mechanisms of RM+NS using computer simulations. In heart of all these simulations you see a fitness functions that *intelligently* selects what should be selected and what should be not. The *designers* of all of these softwares subtly feed their system with external intelligence which normally is not available in the nature. All similar simulations that claim they are correctly mimicing the nature are using a faulty logic. They are deluding themselves into believing that they could invent a perpetual motion machine, but they are not aware that they are subtly feeding the machine with an external source of energy. In this case the perpetual motion machine is the simulation of darwinian evolution and the *external energy feed* is the intelligence that the programmer puts in the fitness function of the simulation. In reality there is no such source of intelligence available in the nature that could replace the fitness functions we see in software simulations. Consequently, there is no simulation of this kind that can expand its complexity forever. All of those simulations are designed to converge to a certain predefined goal. For Dawkins' program the convergence limit was the sentence: "Methinks it is like a weasel". The convergence limit is directly related to the amount of *intelligence* that the fitness function inherits from its programmer.Farshad
June 11, 2006
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I vagely remember studying genetically modified Bacteria that were used to 'digest' toxic spills,the metabolic pathways were engineered,such that they could digest chemicals like toluene,they were introduced to a toxic site and would clean it up and then the introduced populatiion would die out. They died out due to having to constantly produce protiens that no longer could break down there target chemical as it had been used up.The burden of producing a non used protien was too much and spelled the end,the frankenstein bugs could use other sources of nutrition. The point is that every point mutation alters the message and alters the product any computer simulation must have a high degree of resolution,for example :that takes into account changes in protien 3d shape through addition,subtraction,substitution of amino acids,redundancy of the genetic code,interaction of a new product with all the various existing protiens in a cell,just to name a few,never mind about multicellualr organisms! I think this type of resolution is currently not available.In order to boast that it can do the things avida apparently can.WormHerder
June 11, 2006
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GilDodgen wrote:
"I would be curious to see the intimate details of the Panda's Thumb program. I'll bet dollars to donuts that the programmer cheated by defining intermediate fitness goals with the Hello World program in mind. RM+NS in the natural world can't work this way, because it is undirected and without a goal. It is not just blind, but comatose."

If you read Crepeau's paper, you'll see that he is not trying to model real-world natural selection. He is investigating the feasibility of evolving machine language software by random mutation and artificial selection. It's hardly fair to accuse him of cheating "by defining intermediate fitness goals with the Hello World program in mind," when the whole point of the experiment was to openly favor those variations that came closer to producing the "Hello World" string.

Regarding the claims that the program "smuggles" in teleology, the only two fitness criteria it uses are 1) the Hamming distance of the output string from the goal string of "Hello world", and 2) the length of the program producing the string. Nothing in these fitness criteria tells the genetic algorithm how to find solutions to the problem, and in fact different runs will come up with different solutions. It is simply incorrect to argue that the solution is somehow implicit in the fitness criterion and is thereby being smuggled in.

1) the Hamming distance of the output string from the goal string of “Hello world” Oh is that all. And here I thought it was being directed towards a certain goal like "Hello World". Does the program get to buy vowels? Does Vanna White flip the letters over when the program guesses? -ds zapatero
June 11, 2006
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johnnyb - Have a look at Ray's "Tierra" a-life package. This may meet the criteria you're looking for. It would be intersting to see if his results were replicable using a standard instruction set (e.g x86), a bare bones microkernel (e.g. L4) and a minimal supervisor process (to cause radndom changes to memory locations and provide periodic process/memory dumps).Patrick Caldon
June 11, 2006
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"Re #15. I know very little about these programs but my guess is that you are asking them to be a complete simulation of evolution when all they are doing is illustrating some aspect of how complexity can be achieved through trial and success. After all the example that kicked off this thread was hardly an accurate representation of life and yet you felt that there lessons to be learned from it. Comment by Mark Frank — June 11, 2006 @ 3:28 pm" Here's what AVIDA claims to do: http://dllab.caltech.edu/avida/about.shtml "Avida is an auto-adaptive genetic system designed primarily for use as a platform in Digital or Artificial Life research. The Avida system is based on concepts similar to those employed by the tierra program developed by Tom Ray. In lay terms, Avida is a digital world in which simple computer programs mutate and evolve. More technically, it is a population of self-reproducing strings with a Turing-complete genetic basis subjected to Poisson-random mutations. The population adapts to the combination of an intrinsic fitness landscape (self-reproduction) and an externally imposed (extrinsic) fitness function provided by the researcher. By studying this system, one can examine evolutionary adaptation, general traits of living systems (such as self-organization), and other issues pertaining to theoretical or evolutionary biology and dynamic systems. The power of Avida is that it gives us a controllable digital system in which to study the theories of evolutionary biology. Often, we can study elements of evolutionary theory that are difficult or impossible in biological systems."russ
June 11, 2006
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Mark, Isn't the point that even the very best programs we can write cannot create even moderate complexity through trial and success without stacking the deck in their favor? Then imagine how the complexity of life which is 10 to a very large exponent more complex than any of the outputs of these computer programs, could ever arise without also stacking the deck Say by an intelligent designer.jerry
June 11, 2006
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"I know very little about these programs but my guess is that you are asking them to be a complete simulation of evolution when all they are doing is illustrating some aspect of how complexity can be achieved through trial and success." The point is that even if they are a small example of one aspect, the aspect we are asking about is the ability to create specified complexity ex nihilo. I haven't read the methodology on the PT paper yet, but yes, in almost everything the teleology is invariably being snuck in somewhere. I appreciated the use of standard hardware, though. Interestingly, though, no genetic algorithm (that I know of) has yet been attempted where the genetic algorithm itself could be the subject of mutation.johnnyb
June 11, 2006
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Re #15. I know very little about these programs but my guess is that you are asking them to be a complete simulation of evolution when all they are doing is illustrating some aspect of how complexity can be achieved through trial and success. After all the example that kicked off this thread was hardly an accurate representation of life and yet you felt that there lessons to be learned from it.Mark Frank
June 11, 2006
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Re #12: I understand that natural selection requires each step to be functional but not a step toward a predetermined goal. That is my point about why these programs are invalid. Teleology is invariably smuggled into the algorithms. Goals and fitness criteria suitable to reach them are predefined (although sometimes subtly), and intermediate islands of "function" are rigged to be easily reachable by trial and error. The bottom line is that the theory of random mutation and natural selection is dead as an explanation for the origin of life's complexity, diversity, information content and functionally integrated machinery. Actually, it isn't even a theory; it's wildly wishful speculation that flies in the face of common sense and hopelessly huge improbabilities. There isn't a shred of evidence that RM+NS has the creative power attributed to it. This is not science. But it's all the Darwinists have, so it will be defended to the death by any means available, no matter what.GilDodgen
June 11, 2006
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Go away, Blipey (VOICEofREASON). You were one of the first people I put on the blacklist here and nothing has changed. Even before I knew it was you again I didn't approve anything you wrote under this new alias. You are wasting your time. I don't read past the first line of anything you write anymore and no one else sees it at all.DaveScot
June 11, 2006
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Hi Mark, I agree thats why I think the program is too simplistic-each step must represent a functional possible endpoint,each change must also lead to the possibility of differing functions (as demonstrated by co-option and differentiation) because we do not know when the process will terminate,I was asking if that had been factored into the analogy-I dont think it has and so it would need more complexity -leading to a lower probability.WormHerder
June 11, 2006
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Re #10. I think it is the other way round. Natural selection requires that each step be functional but it does *not* require it to be step towards a predetermined goal. That's the whole point.Mark Frank
June 11, 2006
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Hi Guys, Correct me please if I am wrong (im sure you will),but the 'Hello World' program analogy is inadequate for the task of modeling naturalistic evolutionary theory,it is way too simplistic. EACH change of the program must demonstrate a step towards the predetermined goal of the program.This is difficult enough,but within naturalistic evolutionary theory,each individual change no matter how small, must not only be a step in the right direction(retrospectively)but also be functional, and a possible end in its self,as the process is apparently blind. How do you factor in usefulness at each step into this analogy,given that the end of the process is unknown?Is it enough to say that each change toawrds 'Hello world' is analogous to each functional change in naturalistic evolutionary theory?Every small change would possibly indicate a different function (co-option).so I think more complexity needs to be added to this program which of course would result in lower probability.WormHerder
June 11, 2006
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I would be curious to see the intimate details of the Panda's Thumb program. I'll bet dollars to donuts that the programmer cheated by defining intermediate fitness goals with the Hello World program in mind. RM+NS in the natural world can't work this way, because it is undirected and without a goal. It is not just blind, but comatose. Check out my comments on question-begging computer simulations here: https://uncommondescent.com/index.php/archives/802 and Eric Anderson's article here: http://evolutiondebate.info/BitByte.pdf GilDodgen
June 11, 2006
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Hello, Dave! I did not mean to say that Panda's Thumb's response was effective or substantive. I was only giving Gil a friendly "heads-up" that PT had noticed his post and was responding to him. If one uses the Law of Conservation of Information as a book-keeping device (per William), all these over-achieving evolutionary algorithms are indeed shown to be front-loaded one way or another. (Garbage in, garbage out) , or (intelligence in, intelligence out) are indeed the only two fundamental designs algorithms can have. Neo-Darwinists would have us follow the Wizard of Oz' immortal admonition when we evaluate these algorithmic "vindications" of Darwinism: "DON'T LOOK AT THAT MAN BEHIND THE CURTAIN!" :)apollo230
June 11, 2006
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[troll]

How is Gil's claim anything more than your incomplete assessment of PvM's?
It is okay to have Gil put up empty posts, but not anyone else?
Which, of course, brings us to the question of whether or not Pim's post is actually empty.

All that was asked was that the computer program create the Hello World program through RM + NS. The program does EXACTLY this. If you would like to define the parameters of selection, you are free to do so, of course. Now, to be fair, so is anyone else. It would be nice if Pim told us what the parameters of his program were. It would also be nice if you, DaveScot, would present what you think the parameters should be. Then we look at each set and see how well they model a real-life situation.

Either way, the argument you have is not with the program itself, but with what fitness critereon were used. This, at best, highlights problems with an experimenter, and not with the experiment itself.

Now, axe this perfectly legitimate post, which is both lucid and polite. Of course, you aren't looking for lucid posts, or posts that mean anything in general. You are looking to have your ass licked.

VOICEofREASON
June 11, 2006
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But nightlight, have you heard, the Neo-Darwinians have the TRUTH! Therefore, they deserve priority seating at the center of the Great Speck! (make sure your sarcasm-meter is on!) Best regards, apollo230 :))apollo230
June 11, 2006
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