Gil Has Never Grasped the Nature of a Simulation Model

While those credentials are all well and good, they don’t do much to address the substance of the criticisms levelled in the comments of the previous topic.

Gil,

You haven’t addressed the criticisms that Tom, Bill and I raised in response to your last post.

You said

All computational evolutionary algorithms artificially isolate the effects of random mutation on the underlying machinery: the CPU instruction set, operating system, and algorithmic processes responsible for the replication process.

If the blind-watchmaker thesis is correct for biological evolution, all of these artificial constraints must be eliminated. Every aspect of the simulation, both hardware and software, must be subject to random errors.

We pointed out that your statement revealed a misunderstanding of the distinction between the simulator and the thing being simulated.

You are saying that an accurate evolutionary simulation must mutate the underlying hardware and software . But this makes no more sense than arguing that your airdrop simulations are invalid unless you airdrop the computer doing the simulation, or subject the software to temperature variations.

In your simulations, a virtual payload is descending through a virtual atmosphere beneath a virtual parachute, subject to virtual temperature and density variations. The computer itself need not be airdropped nor subjected to real temperatures and density variations.

In exactly the same way, an evolutionary simulation subjects virtual organisms to virtual mutations and winnows them through virtual selection pressures. There is no need to subject the hardware and software to real mutations or errors. In fact, doing so defeats the purpose of the simulation by rendering its results inaccurate.

Your airdrop simulations wouldn’t give accurate results if the hardware and software were mutating underneath them. Why expect an evolutionary simulation to deliver accurate results under those conditions?

Virtual mutations belong in an evolutionary simulation, but real mutations to the underlying hardware and software do not.

I for one would love to see a real discussion about this. I’m a software professional myself but have no special expertise in evolutionary algorithms. I understand that it’s easy to subtly inject front-loaded CSI into an algorithm and that the more sublte the front-loading is the more illusory the end result is in terms of the appearance of chance and selection having created CSI .

I think Gil’s original point was that it is necessary for a simulation to be true to the full range of the possible sources and effects of random mutation and that in the natural world these act on the hardware (physical cells) at a primary level and affect the software (abstract information encoded in DNA) secondarilly . Tom English balked at the suggestion that a serious simulation would need to subject itself to meta-level mutations, insisting that the modelling is an abstraction that brings the entire realm of the system being modelled into the software. I think this is right but that Gil’s somewhat rhetorical point still needs to be considered. That the models themselves (albeit completely manifested in the software) must bring the full range of potential deleterious effects into the picture, in order for meaningful inferences about natural evolutionary systems to be drawn from them.

My question is have there been any case studies in evolutionary computation that have reached towards the level of sophistication in modelling (in software) the full range of effects of random mutation? If so, what are they and what can be learned from them?

josephus63 wrote:

I think Gil’s original point was that it is necessary for a simulation to be true to the full range of the possible sources and effects of random mutation and that in the natural world these act on the hardware (physical cells) at a primary level and affect the software (abstract information encoded in DNA) secondarilly.

If that is Gil’s intent, he should be insisting on virtual errors in the virtual organisms (i.e. virtual hardware) and virtual mutations in their virtual genetic information (i.e. virtual software). The fact that he is asking for real mutations and errors in the hardware and software running the simulation shows that he is confusing the simulator with the simulated.

Here’s my idea for a simulation that might mimic the way that RM & NS are supposed to produce new information:

Our enviroment is a series of, say, ten mazes, with a creature that tries to reach the center. These mazes will consist of simply-connected mazes, and multiply-connected mazes. ( google search if you aren’t sure what these kinds of mazes are )

Our ‘genes’ that gets mutated are the code that controls the movement of the simulated creature. Since we’re simulating how information is supposed to arise in pre-existing organisms, we’ll give it a starting code that guides it through the maze by ‘following the left hand wall’. This will only enable it to solve the simply connected mazes, and not very efficiently (it will go down many dead ends).

The fitness function will consist of counting how many moves it takes to solve each maze, and adding up the total (larger numbers mean a less fit ‘organism’). Unsolved mazes are simply given a very high value (A maze is considered unsolved if it fails to complete it within that number of moves).

For me, to convincingly demonstrate evolution, the resulting code would have to be able to solve the mazes the original could not, and be able to solve other new mazes.

What do you guys think? Would it be a useful model of RM & NS? Would it fulfill my criteria? I predict that it won’t. The most it might do is produce code that solves the simply-connected mazes more efficiently.

That’s you? The OPFOR guys featured your work several weeks ago in a picture essay of an actual drop run from a C-130(if memory serves well) in Afghanistan.

http://op-for.com/aboutus.php

Of course, they also link gratuitous Miss World competitions too, so don’t get to big an ego…

Congrats on a job well done Gil! Please pass along to all your workers and crew in armed services a big thanks too!

well, well, allow me to intercede with a politically incorrect moment of prayer.

May G_d continue to bless your work with extraordinary insight, knowledge, energy and wisdom to overcome our enemy. And may he bless all others accordingly who support our troops in this global war against oppression and ideology of hatred, that which is all things opposed to the love of Christ. For Christ overcomes the world. In Yeshua’s precious name I ask, God raise up whom You will, Amen and Amen.

In general I agree that Gil has overstepped when he suggests that the computer running a simulation must in itself be subject to random mutation.

StephanA: “Our enviroment is a series of, say, ten mazes, with a creature that tries to reach the center. ”

I suspect that you have already front-loaded.

The only destination that RM+NS permits is survival. I think that any artificial “destiny” beyond survival becomes a front-loading.

I think it hard, but possibly not impossible to write a truly not front-loaded simulation. I think that the landscape that must be offered to such as simulation must be the internet itself. If a program was written which reproduced itself, and which had some way of randomly being noticed by human operators, and if the human operators had the privelage of destroying any such program that “got in their way”, the results would be a pretty good simulation. If such a program produced variants which became fun, and extended to start doing real-world tasks, like maybe good quality spam filtering, then I would become convinced that RM+NS can actually account for genuine complexity as seen in nature. Remember, however, that the only thing the program can do is reproduce itself with a certain small error rate. The landscape it is in must contain at least the possibility of affecting the display of the computer it is running on.

Michaels7, mind if I worship the Prince of Peace, rather than claim that my side of a war is somehow divinely right?

Chance never played any role in either ontogeny or phylogeny. The entire evolutionary scenario was planned from beginning to end. Even extinction was part of the scenario. The vast majority of past extinctions were internally produced and had nothing to do even with the accumulation of defective genes. So it was neither bad luck nor bad genes that produced extinctions, to comment on the title of David Raup’s book. Extinction was an orthogenetic, goal directed property of the evolutionary sequence.

I don’t expect anyone to take my views seriously but I will predict with great confidence that no one will be able to demonstrate that I am wrong. It will be, as every other of my several challenges have been, unanswered and probably even unacknowledged. Ideologues are like that don’t you know.

I am convinced that every aspect of phylogeny was predetermined or “prescribed” and that chance played no role in any of it. If catastrophic events had not killed the dinosaurs they would have died anyway. It was part of the program if you know what I mean. All the bizarre ones died and only the conservative crocodilia survived. The same can be said for all the other large animals of the past.

Leo Berg saw this with great clarity:

“The extinction of organisms is due to inner (autonomic) and external (choronomic) causes.”
Nomogenesis, page 407

I wish only that he had used the past tense.

Let me add that the current extinction, the one that Leakey called the sixth extinction, is due entirely to the mindless insistence on the part of civilized man to deliberately destroy his own environment.

I just presented a similar summary over at “brainstorms.” I’ll bet they will both die on the vine.

How do you chance-worshipping, mutation-happy Darwimps like them green apples? I hope they give you a belly ache.

I love it so!

“A past evolution is undeniable, a present evolution undemonstrable.”
John A. Davison

Several points of which to take note:

- Gil’s assertion that simulations are just fantasy, even were it true, has no bearing on the fatal error committed in his previous post.

- Stephen A.’ simulation would not entail operators pushing computers through mazes on rolling tables as they ran the simulation.

- Whatever Gil’s intended rhetorical point, he instead displayed ignorance - plain and simple - of the nature of computation and simulation that this post does nothing to correct.

Scientific American magazine many years ago ran an amusing story (I think it was in an April issue) in which the discovery of an isolated Polynesian island culture was reported. Explorers were mystified by the the ritual behaviors they observed: Island inhabitants pulled ropes that traversed the entire island, ropes that shifted logs from position to position in a huge, island-wide network of ropes and logs. The explorers were astonished to learn that the system performed arithmetic by very slowly executing well known computational algorithms (it has been many years since I read this; some of these details may be misremembered).

This was a spoof with a serious point: although the island was imaginary, real computation could in fact be done using ropes and logs properly arranged. With a large enough rope-log system an algorithm performing, say, long division could be (slowly) executed.

More importantly, the same algorithm for division yields the same result by means of the same steps when performed by a person using pencil and paper, when coded in Basic and run on TI 99/4a, when executed by a quantum computer, handled by Searle within his Chinese room, and indeed when performed “mentally” within the working memory of an individual person. The logic of the algorithm is utterly independent of the particulars of the physical substrate on which it is executed (even if that substrate is itself computationally simulated.)

The point is that the logic of algorithmic computation (including simulation) is independent of the substrate on which it is instantiated. Damage to hardware occurs at a logical level removed from that at which the algorithm is expressed. Similarly, a simulation operates at a level utterly removed from the hardware that hosts the simulation.

If you don’t get this, well, you don’t get it.

Bfast,

“Michaels7, mind if I worship the Prince of Peace, rather than claim that my side of a war is somehow divinely right?”

Not at all, please read my prayer again. I did not ask for my will to be done, but the Fathers - “raise up whom You will.” That includes intelligent troops that can negotiate peacefully in these regions, because wisdom is required for peace, not war. I do not link prayer only to destruction of our enemies.

And my prayer is one of protection too - for all.

Those drop offs guided from the C-130 go to Afghanis as well as our troops. Medicine is delivered to sick children, vaccines, food and so many other items needed to help not only protect our troops but to help the people themselves they are trying to free from oppression.

If you think the Taliban do not oppress, torture, or murder and are equal to our cause and that of our troops, then we do disagree. I believe these efforts and the sacrifices our troops are making are a worthy cause and I certainly believe that most of them have a higher cause in their hearts than someone who burns down schools, indoctrinates children with hatred, oppresses and murders women for any number of fallacious reasons, and blows up civilians on purpose.

Does that make our cause divine? Only the Lord can make such judgements, but my prayer is that it is in His will.

When I pray the enemy does not come against the love of Christ and that He overcomes the world, I am in fact asking for His Word, His love to conquer their hearts, and not by mens weapons. When I pray against an ideology of hatred and oppression, I am praying against principalities and powers, not people, who are sheep that God calls. I pray for all people to be saved, not just Americans. This is what is in my heart.

I pray for Iraqis and Afghanis to have peace for their children’s future. And I hardly think myself divine after my life of debauchery, my side or this nations.

But it is important to note in reading the Psalms, King David did not pray for defeat and I find it quite hard to do so myself. And from my understanding, Christ liked his music and so did His disciples as they quoted them often. One can pray for victory in many ways, without wishing harm on innocents.

In truth, the love of Christ will never happen if those trapped in nations controlled by dictators or false teachers who do not allow them to hear the Living Word. One cannot come to Christ without hearing.

We worship the Prince of Peace together, but He is also the Son of the Lord of Host - Captain of Armies, King of Kings, and Lord of Lords, and Healer, Counseler. He has many names. And one period of His rule will be with a Rod of Iron.

Repentence is another thing altogether… and one of which I often need to do. As well as this nation needs to as well. But that is politically incorrect also

And I have taken this post off course, so my apologies to Gil.

Michaels7, I personally have been very troubled by the American Christian communty’s belief that America is somehow “in the right” with the authority of Christ himself, and its enemies are “in the wrong” with the same authority. The fact that the USA has abandoned long held values of justice as exemplified by Guantonimo bay and the “secret” CIA prisons seems to be somehow justified. The fact that the stated reason for invading Iraq, namely because of Sadam’s aledged secret WMD programs, has not been validated does not seem to faze the Christian community one bit. “We support the decision of our leader. Bush is a man of God who is making righteous war on our enemies” is the cry of the religious right. I find it disgusting, horrifying, that the religious right would label this war and the actions at Guantonimo bay as “approved” by my creator.

Several points of which to take note:

- Neither Gil’s technical accomplishments, nor his assertion that simulations are just fantasy, have no bearing on the fatal error committed in his previous post.

- Stephen A.’ simulation would not entail operators pushing computers through mazes on rolling tables as they ran the simulation.

- The thread has seriously wandered off topic and onto the domain of prayer, while on-topic posts are (apparently) blocked by the Nixplanatory filter that governs the exchange here.

Scientific American magazine many years ago ran an amusing story (I think it was in an April issue) in which the discovery of an isolated Polynesian island culture was reported. Explorers were mystified by the the ritual behaviors they observed: Island inhabitants pulled ropes that traversed the entire island, ropes that shifted logs from position to position in a huge, island-wide network of ropes and logs. The explorers were astonished to learn that the system performed arithmetic by very slowly executing well known computational algorithms (it has been many years since I read this; some of these details may be misremembered).

This was a spoof with a serious point: although the island was imaginary, real computation could in fact be done using ropes and logs properly arranged. With a large enough rope-log system an algorithm performing, say, long division could be (slowly) executed.

More importantly, the same algorithm for division yields the same result by means of the same steps when performed by a person using pencil and paper, when coded in Basic and run on TI 99/4a, when executed by a quantum computer, handled by Searle within his Chinese room, and indeed when performed “mentally” within the working memory of an individual person. The logic of the algorithm is utterly independent of the particulars of the physical substrate on which it is executed (even if that substrate is itself computationally simulated.)

The point is that the logic of algorithmic computation (including simulation) is independent of the substrate on which it is instantiated. Damage to hardware occurs at a logical level removed from that at which the algorithm is expressed. Similarly, a simulation operates at a level utterly removed from the hardware that hosts the simulation.

This is what some here seem not to grasp.

But Bush IS a man of God who is trying to establish a democracy in the middle east and nothing Bruce Fast or anyone else can detract from that very worthwhile venture. I wish him well.

How do like them apples Bruce? I hope it gives you gas.

“A past evolution is undeniable, a present evolution undemonstrable.”
John A. Davison

Nice to see this thread hasn’t gone off topic.

John A. Davison, “I hope it gives you gas.” It does.

DS:

“It’s all well and good to model it but you still have to build the real thing to see if it works.”

Your reply doesn’t go to the point of my post, which is that the logic of algorithmic computation (including simulation) is independent of the substrate on which it is instantiated. This is true for all computation - not just modeling and simulation (e.g. for arithmetic computations). Hence the long division algorithm of my example remains logically unchanged across the many media (pencil and paper, 99/4a, quantum computer, banks of vacuum tubes, frontal lobes, etc) on which it can be instantiated. This independence is what makes Gil’s original suggestion vis mutating the hardware of a computer running an evolutionary simulation rather silly. This has been stated and illustrated many ways in this (and the previous) thread.

I didn’t intend the rope-log computer as an analogy to something simulated - rather, the spoof illustrates this independence of computation and the physical substrate hosting omputation. We already know that computation can be hosted by virtually any medium, and that the rope-log computer could be made to work. (Whether it would be practical is an entirely different question.)

StephenA - If you Google “genetic programming maze” you’ll find several sites devoted to this subject. At least one seems to let you design your own maze.

bFast - what’s important to NS is differential survival. That is usually modelled as scoring well at some task. If only two states are allowed, you’ll still get progress, but slower than with a finer grained scale.

It is also possible to claim that there is front loading in the choice of instruction set (this is in referenece to GP systems, such as StephenA was speculating on). A way to avoid this is to give a GP system a random instruction set which may or may not include the operators that the researcher knows a priori are useful. All this does is slow down the system, it doesn’t stop it from eventually finding better and better solutions.

DS - Avida isn’t a CA, AFAIK.

On the other thread, Tom English wrote:

Teaching computer science students from the undergraduate to the doctoral level, I encountered quite a few who were excellent programmers, but who could not begin to comprehend the notion of a model. The concept is simply too abstract for some people. They never catch on to it.

Tom,
You’re absolutely right. As Gil demonstrates, some people never get it, even after having it repeatedly explained to them.

Gil wrote:

One other obvious point: A simulation must accurately depict the system being modeled. The computational machinery and information content of biological systems is inherent in, and quintessentially critical to, the function of the system being modeled, and therefore cannot be excluded from the effects of mutations, without the simulation being rendered completely meaningless.

Gil,
Let me make this as clear as I can:

1. Yes, the reproductive apparatus of life is (in part) an information processing system.
2. Yes, the computer and software running the simulation are also an information processing system.
3. No, they are not the same system. In an evolutionary simulation, one of them (#2) is simulating the other (#1).
4. Yes, a completely realistic simulation of evolution should include mutations of the reproductive apparatus being modeled(#1).
5. No, this does not mean there should be mutations of the computer and software running the simulation (#2).

Do you see the difference?

Let me try again using your example of autonomously guided airdrop payloads.

1. The guidance computer and software on one of your airdropped payloads form an information processing system.
2. The computer and software you use to do an airdrop simulation also form an information processing system.
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.
5. You would not introduce errors into the computer and software running the simulation.

Errors in the hardware and software of the simulator only serve to produce nonsensical simulation results. If you introduce an error into the simulator’s operating system, you won’t be able to trust the results of your simulation. This is just as true of an evolutionary simulation as it is of an airdrop simulation.

Finally, just to really hammer the point home: the simulator and the model are separate. I can simulate a broken microprocessor chip on a perfectly functioning computer. You can simulate a failed airdrop on a perfectly functioning computer. We can simulate DNA copying errors using a perfectly functioning computer. The simulator and model exist at different levels. Errors in the model do not require errors in the simulator.

Sorry to go on so long, but it really seems that the message won’t get through if it isn’t spelled out ultra-explicitly.

StephenA-

Here’s my idea for a simulation that might mimic the way that RM & NS are supposed to produce new information

In some sense, this suggestion is not very useful as long as Gil and other IDists believe that software and hardware must undergo mutation. If we treat their suggestions seriously, no simulation at all can occur. Sure, we know they’re wrong, but it’s also important to show them that they are wrong. Failure to do that means that they will continue to erroneously play the “simulations don’t mirror actual reality” card, which may be convincing to people who don’t know better.

I’ve thought about creating evolutionary simulations which involve entire ecosystems (letting natural selection rather than an explicit goal act as the selector). Part of me thinks that it’s a waste of time because I know that ID advocates will always come up with some reason to dismiss the software. To put it another way: there is no conceivable simuation which could satisfy ID advocates. IDists may disagree with this, but the suggestions that involve destruction of the computer which runs the simulation or suggestions that are far outside of our compuational power (protein folding) end up preventing any “accurate” simulation from happening at all.

DaveScot -

An example of a real honest to God biological simulation is protein folding. It’s something of a holy grail.

But, that’s really overkill. Sure, you can say that we need to mirror the real world all the way down to the protein-folding level. (Nevermind my earlier point that we have nowhere near the computational power to do so - the “Folding at Home” project has massive computing power being put into this, and they’re nowhere near the needed computational power. An evolutionary simulation that does this multiplied by billions of organisms over billions of years is clearly out of our reach. Further, even if it were done, I suspect it would be attacked with claims that information was subtlely smuggled in, that the simulation was “intelligently designed” and therefore useless, or (as Gil claims) that the software and hardware must be subject to mutations as well.) But, it’s overkill to do this if you simply want to show that RM+NS is capable of producing information. That point can be shown through simple genetic algorithms; no need for simulation down to the protein-folding level if you want to bust the argument that RM+NS can’t produce information. If your argument is that something else confounds the evolutionary process somewhere else, then maybe a system capable of doing protein-folding would be useful. But, to break through the claim that “RM+NS can’t produce information/CSI”, it’s overkill.

As far as genetic algorithms are concerned, I think it’s already clear that they do produce information - the main question is how do we show that to people who resist this conclusion or have intellectual hangups or misunderstandings somewhere?

I am beginning to think that evolution WAS entirely the loss of potentiality. There is no evidence that any contemporary organism is capable of ever becoming anything different from what it is right now. Furthermore, there is no evidence in the past for any such event even though I know it must have taken place. I conclude that the “evolvers ” are all gone by the wayside and we are left with only the products, all of which are doomed to extinction.

How does that grab you?

“A past evolution is undeniable, a present evolution undemonstrable.”
John A. Davison

bfast — In general I agree that Gil has overstepped when he suggests that the computer running a simulation must in itself be subject to random mutation.

Wouldn’t that depend on what degree of evolution that you are trying to model? If one is trying to demonstrate how life occurred without intelligent design, it should be recognized as axiomatic that you can’t you do so using intelligent design which obviously includes hardware and software. OTOH, if one is trying to demonstrate evolution with intelligent design, then simulation programs will make sense. Further, the more the ID the more rational the evolution.

“We support the decision of our leader. Bush is a man of God who is making righteous war on our enemies” is the cry of the religious right.

Where the heck are you getting this from??? Anyway, isn’t the war was supposed to be some kind of neocon (Jewish) conspiracy

And my last sentence was sarcasm, in case anyone misses that.

The point is that the logic of algorithmic computation (including simulation) is independent of the substrate on which it is instantiated.

As an undergrad at MIT, Danny Hillis and teammates implemented a tic-tac-toe player in Tinker Toys. It was guaranteed never to lose a game. I am sure there are some here who would say, “How can tic-tac-toe be played with Tinker Toys? You have to write on a piece of paper to play the game.” This reflects a common deficit in abstraction. One can as represent the game state in Tinker Toys as well as one can with marks on a piece of paper.

bFast,

You’re a great example of why I can’t make ID-NDE into a litmus test of the decency of a person. Thanks for your posts.

It’s all well and good to model it but you still have to build the real thing to see if it works. That’s how models work. You don’t seem to understand that. Once you build it and it works as the model predicted then you have a working model, until then you have an untested model. Capisce?

Proof of principle does not require a fit to data. We often see here claims of what random mutation and natural selection cannot do, and evolutionary computation puts the lie to those claims. It does not matter one whit whether the simulations fit biological observations. If you read the writings of Bill Dembski, you will see that he understands as well as I do that the essential questions regard informational physics, not biosystems per se.

If it flies, the simulation was good. If it crashes, the simulation was bad. Everything else is irrelevant.

An extremely limited notion of what a simulation can teach us. Read post 31.

The computational machinery and information content of biological systems is inherent in, and quintessentially critical to, the function of the system being modeled, and therefore cannot be excluded from the effects of mutations, without the simulation being rendered completely meaningless.

Ah, Gil, but what you seem not to comprehend — this, I think, is a genuine misunderstanding — is that there is no absolute distinction between an analytical model and a simulation model. And if simulation models suffer the defects you say they do, then Bill Dembski’s abstract models of evolution in Searching Large Spaces and The Conservation of Information are in even bigger trouble. By the way, consider that I published on conservation of information in search in 1996, ten years in advance of Bill’s dissemination of “The Conservation of Information.” I can tell you that the analytic models are not as detailed as the simulation models. The very reason we implement some models as computer programs is that they are not amenable to mathematical analysis.

You cannot dismiss simulation models of evolution as simplistic without doing the same for Bill Dembski’s and my own analytic models. Sure you want to do that? It doesn’t seem wise to me.

DS said:

“The substrate doesn’t matter if you’re not modeling reality. If you’re modeling reality then the substrate of reality is a benchmark by which all others are measured.”

You miss what I intend by substrate, and are using “substrate” with a different referent than am I. I am referring to the computational system capable of hosting the abstract collection of algorithms that compose the simulation. As pointedly illustrated above, this hardware may be composed of Tinker Toys, paper and pencil, hand calculator, ropes and logs, tunneling quantum events, etc. The logic of the algorithm that runs on these various physical substrates remains constant as the substrates vary.

Using “substrate” in the sense I intend, as defined above, the assertion that an algorithm is independent of the particulars of the computational substrate is as true when simulating a system that exists in reality as when modeling hypothetical events for theoretical purposes.

To return to my original example, the computational algorithms that compose a model of an approaching, very real hurricane are as independent of computational substrate as is any evolutionary algorithm run as a theoretical exploration. In the instance of a hurricane simulation you will indeed want to test the predictions issued by your model against the behavior of the actual hurricane, not the least for the purpose of improving your model. Same with Gil’s simulation of the process of dropping guided packages. Nevertheless, these simulations, whether of hurricane or guided package, run at a computational level that is utterly independent of the hardware that hosts those simulations. The computational substrate is not part of the simulation - nor is it the reality against which the results issued by the simulation are tested.

You use substrate in the sense of the “system that is being simulated and the reality within which it is embedded.” This is not the substrate to which I refer. As you say, this reality is of obvious relevance when testing for accuracy the results issued by a simulation. But this is not the computational substrate to which we are referring.

BTW, the assertion that it is necessary and desirable to simulate every detail of the system and every level of the system being modeled is misleading. This depends upon the purpose served by the simulation. For example, if I am simulating airfoil shapes to determine which yield the least drag and the greatest lift, it is perfectly legitimate to omit modeling of the interior structure of the airfoil. OTOH, if I am modeling the performance under flight stress of an airfoil destined to be built and installed on actual aircraft that internal structure becomes relevant. So the level of detail required is determined by the purposes served by the simulation. And, often times, one wants to pare one’s simulation down to simple terms for the purpose of better understanding the phenomenon being modeled.

DS:

“Here’s yet another real, testable model that interests me: Stellar Evolution.”

Your distinction between models that are testable against empirical observations of some reality (actual stellar behavior) and those that are theoretical explorations certainly legitimately points to different sorts of simulation that serve different sorts of purpose (although the question of to which class of simulation evolutionary models belong is another debate). But your legitimate distinction doesn’t speak to the problems with Gil’s original proposal.

Gil insisted that random modifications (a feature of a computational model of NS) extend all the way down into the hardware on which that simulation is run (the computational substrate) before the evolutionary simulation is complete.

This is just plain wrong.

Nor does it accomplish what I think Gil and maybe you are reaching for - a test grounded 3-space reality of an evolutionary simulation. His proposal simply does not pose that test.

Dave Scott,

I’m growing very frustrated by you and others’ inability to grasp the fact that models of reality need to be testable.

I have long been frustrated with certain parties’ inability to recognize that neo-Darwinian evolution is an abstract process, not necessarily implemented in biota.

In 1995, I ran an evolutionary computation on a massively-parallel computer and obtained more than 20 thousand models predicting annual sunspots counts. The series of sunspots counts is chaotic, and has been a challenging benchmark problem in time series prediction for many years. With a combination of models, I obtained far better prediction accuracy than anyone else ever had (“Stacked Generalization and Simulated Evolution,” BioSystems, 39(1), pp. 3-18, 1996).

My question for you is how I did that. I had and still have zero knowledge of sunspot formation. To my knowledge, nobody understands the blasted things. How could I have front-loaded the evolutionary computation when no physicist or statistician had ever managed to give a good model of the time series? I can see no way that you can attribute the success of the evolutionary process to my intelligence.

The point I want you and others to get here is that such successes of evolutionary computation demonstrate the efficacy of abstract neo-Darwinian processes. Again, if this says nothing about evolution, then neither do Bill Dembski’s models of assisted search and added information. How are you going to rule out my work without ruling out his? Direct question.

I’ve given you examples of real models in biology (protein folding), mechanical design (aircraft), and electronics (microprocessors). These all model the real world and can be tested by seeing if they duplicate the results obtained in the real world.

Modeling always entails a choice of granularity. No one, but no one, simulates microprocessors at a fine level of granularity. The computational demands are too great, as you should know. 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. As for aeronautics, let’s consider airfoil design instead of mechanics. Simulation is very useful in that domain, even at high Reynolds numbers. But if you ask someone to give you a precise prediction of airflow, he or she will not be able to give it. The simulations are qualitatively correct, but not quantitatively. In other words, simulations used to design airfoils cannot give the kind of predictions you demand of evolutionary simulations.

It seems I am wasting my time with this thread also.

I did manage to flush out a Darwimp in response to my several papers. Just click on John A. Davison on the side bar and join the fun.

The more the merrier I always say.

SOCKITTOME!

I love it so!

“I’m an old campaigner and I love a good fight.”
Franklin Delano Roosevelt

“There is nothing more exhilirating than to be shot at without result.”
Winston Churchill

“Darwinians of the world unite. You have nothing to lose but your natural selection.”
after Karl Marx

“A past evolution is undeniable, a present evolution undemonstrable.”
John A. Davison

Tom,

I think that DaveScot is making the following point. EC has abstracted evolution out of one description of biological reality. It has been successful in using that abstraction to attack problems. Only some EC researchers attempt to explain anything about biological reality, most are happy with having a useful tool to use on other problems. But to reconnect to biology, you have to ensure that you didn’t abstract away the wrong things in the first place. One way to do that is to do very little abstraction. DS, am I close?

There ar people using to GP to work on protein folding problems.

Tom English // Oct 1st 2006 at 7:12 am

bFast,

You’re a great example of why I can’t make ID-NDE into a litmus test of the decency of a person. Thanks for your posts.

Tom, this is a bit shocking. I’ve been to Pandas Thumb and seen the sneering insults that are smattered about. But it never occured to me that belief in ID-NDE might be a litmus test for “the decency of a person” (I know it’s not your litmus test, but apparently the idea occured to you).

The only realm in which I see this kind of litmus test for decency is liberal politics, in which liberals often believe conservatives are evil, but conservatives generally believe liberals are merely mistaken or foolish. Since I believe you identified yourself as a college professor (i.e. someone toiling deep in the heart of political liberalism), that explanation for your comment to bFast seems to fit. Am I mistaken?

Sorry, my comments start with “Tom, this is a bit shocking…”

Tom English,

bFast,

You’re a great example of why I can’t make ID-NDE into a litmus test of the decency of a person. Thanks for your posts.

Good trick. I, an IDer, have been suggesting that a couple of other IDers on this site are viewing an issue with an opposite moral position to my own.

If IDers hold opposite moral positions on any given issue, then your litmus test is bogus, isn’t it.

Further, I personally agree with many issues held by the religious right. I only fail to understand how the religious right has adopted a love for war. They certainly didn’t get it from the New Testament that I read.

Tom English says:

Proof of principle does not require a fit to data. We often see here claims of what random mutation and natural selection cannot do, and evolutionary computation puts the lie to those claims.

And what is that principle? The implication that EC in general involves “natural selection” seems to be quite a stretch.

Natural selection is very real. Today, as in the past, it PREVENTS change. That is all it ever did. Don’t take my word for it. You never do.

“The struggle for existence and natural selection are not progressive agencies, but being, on the contrary, conservative, maintain the standard.”
Leo Berg, Nomogenesis, page 406

“Animals are not struggling for existence. Most of the time they are sitting around doing nothing at all.”
John A. Davison

Any student of the living world knows that. Accordingly, Darwinians are not students of the living world.

How does that grab you Darwimps? I bet it smarts a little eh? I certainly hope so.

I l0ve it so!

“A past evolution is undeniable, a present evolution undemonstrable.”
John A. Davison

Earlier I wrote:

And if simulation models suffer the defects you say they do, then Bill Dembski’s abstract models of evolution in Searching Large Spaces and The Conservation of Information are in even bigger trouble.

Some of you are avoiding the crucial point that the leading theorist of the ID movement focuses much more on probability and information than he does living things. If you look at the papers I linked to, you will see that Bill says nothing about protein folding and genes and chromosomes and predators and plagues and earthquakes and meteors. He models information flow that has never been observed directly. There are no data for his models to fit, and he gives no guidance as to how to validate the models. If biological realism were as crucial as you say, Bill would be in bad shape.

Tom English says:

If biological realism were as crucial as you say, Bill would be in bad shape.

Well, let us look at the first Dembski article you reference.

1 BlindSearch
Most searches that come up in scientific investigation occur over spaces that are
far too large to be searched exhaustively. Take the search for a very modest
protein, one that is, say, 100 amino acids in length (most proteins are at least
250 to 300 amino acids in length). The space of all possible protein sequences
that are 100 amino acids in length has size 20100, or approximately 1.27×10130.

Actually, he references the biological context right up front. Now certainly this doesn’t prove anything about the underlying issue, but it does frame the difficulties for a simple RM&NS. Now, biological realities may include some convenient arrangement of the landscape, or maybe some sort of life-friendly self-organization that remains as yet undiscovered. I’ll let the reader decide whether those possibilities favor a claim of “victory” by either side of the debate, but will merely point out that with regard to simple claims of RM&NS, known biological practicalities make Dembksi’s arguments the easier road to travel, so he is unlikely to forsake them as you claim.

Tom,

It seems to me Dembski isn’t really modelling, is he? I’m no math geek, nor am I an uber programmer geek, so I assume I’m missing something obvious and hope you’ll correct my error.

Is WD really modelling when he takes what is there - eg, a 100 amino acid protein sequence - and determines the statistical search space accordingly? That seems much different than setting up an digital ‘environment’ to demonstrate evolution. What am I missing?

Roger,

Yes, Bill gives a made-up problem of searching for a particular sequence of amino acids. He does not go at all into the complexities of how amino acids specify proteins. And he certainly does not mention that in reality many permutations of an amino acid sequence may represent the same protein, and that numerous proteins are represented by amino acid sequences of length 100.

So what Bill does is no more than to indicate that search for some biological structures takes place in combinatorial spaces. The mention of amino acid sequences does not embue his work with biological realism. The paper would be unchanged if the problem were to search for a sequence of 100 letters (the size of the search space would go from 20 ^ 100 to 26 ^ 100).

todd:

It seems to me Dembski isn’t really modelling, is he?

Let’s focus on “Searching Large Spaces.” He gives a model of search for a small target in a large space. He calls that model assisted search. Late in the paper, he indicates that natural evolution must have been an assisted search. That is, his claim is that one can model natural evolution as assisted search.

Is WD really modelling when he takes what is there - eg, a 100 amino acid protein sequence - and determines the statistical search space accordingly?

He’s not trying to solve that particular problem. It’s just an example to motivate his analysis of assisted search. His mathematical results are applicable to a large class of problems.

David vun Kannon wrote:

…to reconnect to biology, you have to ensure that you didn’t abstract away the wrong things in the first place. One way to do that is to do very little abstraction.

Less abstraction isn’t necessarily better. The more concrete the model, the longer it takes to run. A hurricane model that tracked the path of every air and water molecule would be quite concrete but worthless for forecasting, because it would run so slowly that its forecasts would turn into retrocasts.

Less abstraction doesn’t necessarily mean better accuracy, either. A model of the soybean market that attempted to track the activity of every neuron in the brain of every farmer, trader, and consumer would degenerate into an incoherent mess, whereas a more abstract model could yield useful results.

The evolutionary models that are out there are not attempts at “photorealistic” simulations of evolution. Nobody expects to see one of them reproduce the marsupial/placental split, for example. They are instantiations of abstract Darwinian processes (replication, variation, selection), and their purpose is to yield information about the capabilities and limitations of Darwinian processes. Biological evolution is just one instance of a Darwinian process. Whatever we learn about Darwinian processes in general applies to biological evolution in particular.

The significance of Avida, in particular, is as an example of how a Darwinian mechanism can produce irreducible complexity. Honest critics can no longer claim that NDE cannot in principle produce IC. They must show that a particular IC structure cannot be produced because of the particular local genomic and fitness landscapes.

This is a blow to the many ID advocates who saw the existence of IC as proof of design.

John Davison wrote:

Natural selection is very real. Today, as in the past, it PREVENTS change. That is all it ever did. Don’t take my word for it. You never do.

Ok, John, since you’re feeling neglected, I’ll take your bait. How do you explain nylonase, given your belief that natural selection is solely conservative?

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.

Secondly- I’d bet that a lot of people here and others in ID, in general, would disagree that avida shows what you claim. Even if it did show this in a computer simulation, again- it’s not the real world. On top of that- I’d say a lot of honest IDers would disagree with you and do so honestly. It doesn’t make a person dishonest to discount avida as a fantasy.

Because a computer simulation purports to show something is possible doesn’t mean it’s possible or anywhere near possible in the real world.

Does the above hold for a mathematical model which says that something is impossible (or as good as) as well?

Karl Pfluger

Nylonase is an enzyme, not an organism. Adaptive enzymes have been known for decades and probably have nothing to do with creative evolution.

Does that help? Probably not.

I am not neglected. I am cynically and deliberately being ignored. So also were my sources and they still are. We are ignored because collectively we have exposed and destroyed the biggest hoax in the history of science. Got that? Write that down.

Thanks for posting and exposing yourself.

I love it so!

“A past evolution is undeniable, a present evolution undemonstrable.”

Dr Davison,

You sir, are an iconoclast of the highest order! Got that? Write it down!

I think I had better clarify what my suggestion was for since BC seems to think I’m against ID.

I think that it is possible to simulate the effects of RM & NS in a computer model, and my suggested model was an attempt to do that. 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. I think most ID supporters agree with me here (if you don’t, let me know). What I contend is that the simulated models that are supposed to produce new information from mimicing evolution do not in fact accurately simulate RM & NS.
If I understand correctly, some here also contend that no simulation is capable of producing new information. They may be right, but I don’t know enough to argue that case, so I leave that area alone.

I hope it is clear what I am saying, and what I am not saying.

P.S. I am just an interested layman who dabbles in programming, so please keep your replies as free of jargon as possible.

Todd

Thanks for the compliment. Iconoclasts seek to overthrow established order. That is the purpose of science now as in the past. Thanks again.

I love it so!

“A past evolution is undeniable, a present evolution undemonstrable.”
John A. Davison

Tom:

Isn’t what Dembski is doing different than Avida or other Evo-sims are doing? It seems to me you are misstating Gil’s point of contention regarding evo-sims.

Karl:

Avida proved IC can arise without intelligent cause? So then, what caused Avida? It seems an impossible task to create a program, especially one which purports to ‘prove’ stochastic evolution, and keep the marks of intelligence out of the picture. This is the bill of goods ‘your side’ is selling - it is counter-intuitive, so I hope you understand how laymen such as myself consider such a claim with great skepticism.

Here you have creators (programmers) defining the ground rules of the Avida universe, which you say produces IC, refuting IC as a hallmark of intelligent cause - yet… you have no universe to produce the IC without intelligent agents defining the terms!

Is there some way to resolve this paradox and leave your claim standing? I’m eager to hear it!

StevenA: Re: #56

Ditto that for me. I’m not a math geek like Dembski nor a uber goober programmer geek like Gil - I don’t ask for ID for Dummies, just minimal mumbo jumbo and gobbledy gook!

Dr Davison:

I’m glad you recognized it for what it was…and it didn’t give you gas! Heh.

Tom English:

I have long been frustrated with certain parties’ inability to recognize that n