The Evolution of Cooperation: Hawks, Doves, Ravens and Starlings

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The evolution of cooperation has long been a vexing problem in biology. In the 1960s and later, a number of proposals to account for various forms of cooperation were offered, including group selection, kin selection, and reciprocal altruism. Both kin selection and reciprocal altruism have some biological data to which to appeal. In The Selfish Gene Dawkins argued that cooperative behavior could emerge as ‘selfish’ genes evolved in the context of other genes (indeed, he’s said that the book could have been title The Cooperative Gene with no change in content) and to the extent that cooperation is an effective strategy for gene vehicles (organisms) to increase reproductive success, but that was largely a formal argument rather than an empirical one. And group selection (which Dawkins emphatically rejects), in my view at least is still on shaky empirical grounds. (Apologies to Steve Rissing, a friend and Project Steve Steve with whom I argue about that.)

A difficulty of doing research on cooperation is the same difficulty that plagues much research on other complex evolutionary phenomena, namely time: interesting multi-celled animals have (relatively) long lifetimes and following a population for many generations is impossible for a single researcher.

Enter computer models. I will not here rehearse the history of computer modeling of evolutionary processes, since I’ve previously touched on it here, here and here on PT.

Of present interest is a study of the evolution of cooperation in a computer model of evolution. Prior work has shown that there are conditions in which several kinds of ‘strategies’ for interactions among artificial agents can evolve. Robert Axelrod, for example, has done a slew of work on that topic. Game theory informs much of that research, and has been useful in predicting the occurrence of certain kinds of strategies in multi-agent contexts.

A new study by Mikhail Burtsev & Peter Turchin (Nature, 440:1041-1044, April 2006) provides a good deal more insight into how cooperative strategies can evolve.

More below the fold.

Burtsev & Turchin employed an agent-based model with artificial agents – what I will hereinafter call “critters” – having a structure in which a single-layer neural net connects inputs (receptors) to outputs (effectors). Receptors carry information about the external state of the critter’s world and about its internal state. The single-layer neural net, with variable (and mutatable) weights, connects inputs to outputs, producing behaviors.

The critters’ world is a 2-D 30x30 grid of cells with the edges connected to form a torus. Each cell contains a resource bundle (renewed periodically) and some number (which may be zero) of critters. There is no limit to the number of critters that can occupy a given cell; food, not space, is the limiting resource in this model. Each cell receives a periodic fixed amount of food, the replenishment and allocation of food being non-contingent. Critters have an orientation in a cell – there is a ‘forward’, ‘left’, ‘right’, and ‘back’. A critter can sense whether there are other critters or food in its own cell, and can sense the contents (other critters and food) of the immediately forward cell and the cells to the immediate left and right. They can’t sense behind them; their ‘field of view’ is limited. Critters can consume the food, increasing their internal resource value. In addition, a critter can sense the level of its internal resource: in effect, it can tell when it’s hungry.

Each critter carries a “marker” – a heritable externally ‘visible’ 10-digit integer string that identifies its lineage – a new critter’s marker is inherited from its parent when the parent divides. Thus there is information in the environment that distinguishes between kin and non-kin. A critter’s sensory system can calculate the Euclidean distance between its own marker and that of other critters in its field of view.

Initially the critters have just three “pre-wired” actions available to them: move into the forward cell if ‘food’ is there; eat if ‘food’ is in the current cell; and divide otherwise. Every action (except eating) depletes the critter’s internal resource, which must be replenished by eating. When a division occurs, the offspring is placed in the same cell as the parent. The offspring ‘inherits’ half of the parent’s internal resource and its marker. All other weights in the receptor-action matrix were set to zero initially.

In the evolutionary procedure of the study, mutations can occur in the weights of the single-layer neural net that connects receptors to effectors during division, and thus receptors can be connected to actions in new ways and new combinations, and previous weights can be altered. As a result, it’s possible for previously innocuous stimuli to come to induce behaviors.

The study had two main conditions: detectable markers vs. undetectable markers. No previous work with agent-based simulations of which I’m aware has employed critters who carry heritable phenotypic markers perceptible and discriminable with respect to self by other agents, though there may be some such out there somewhere. In that history of research where agent phenotypes are indistinguishable, three main ‘strategies’ for interactions among agents recur: hawk, dove, and bourgeois. In the hawk strategy, agents cross cell boundaries to attack other agents, stealing their victims’ resources. Doves never attack and attempt to escape from other agents when the ‘see’ them. A bourgeois agent stays put in its home cell, and attacks invaders of that cell while ignoring critters in neighboring cells.

In Burtsev & Turchin’s no-marker condition, those three strategies did indeed emerge: the population evolved critters with all three strategies. Whether the bourgeois strategy evolved depended on the food supply to cells; below some critical value, too low to support a sedentary critter, only hawk and dove evolved. When food supply is sufficient, the bourgeios strategy comes to dominate the population.

In the second and most interesting experimental condition of the Burtsev & Turchin study, marker recognition was turned on, so the potential for discriminating similar-to-self from dissimilar agents was available. In that condition, three strategies not heretofore seen evolved: cooperative dove, starling and raven.

Cooperative doves ignore out-group critters bearing markers dissimilar to their own, but ‘cooperate’ with in-group critters by leaving cells with other doves bearing similar markers to avoid competing with them for food. Ravens similarly leave cells with similar in-group critters, but they also attack dissimilar critters when they are encountered. Starlings stay at home with in-group critters, but as a group attack interlopers much as real starlings mob an invading hawk or owl.

That is in itself very interesting, but also interesting is the interaction of the evolution of particular strategies with the level of food resources – cell carrying capacity. As noted above in the non-marker condition, when the carrying capacity of cells is low, the bourgeios strategy does not emerge because the food supply of a given cell is insufficient to support a sedentary critter producing offspring in the same cell. Similarly, in the condition with phenotype markers available but insufficient per-cell resources, the starling strategy is impossible because cells can’t support multiple critters. But the raven strategy is possible in that situation. If the carrying capacity of cells is sufficient to support multiple critters per cell, then the starling strategy can and does arise.

Burtsev & Turchin mention that group predation – essentially hunting as packs, the “wolf” strategy – did not arise, most likely because the critters lacked effectors that allowed traveling in groups. They plan further research to explore that issue.

To finish I’ll quote Burtsev & Turchin’s concluding paragraph:

In conclusion, our study shows that within the artificial evolution framework it is possible to model not only how one strategy displaces another (or not), but the very process by which new strategies emerge out of a very large space of possibilities. Our model did not endow agents with a set of preconceived strategies – all that we assumed was that agents have a set of elementary sensory inputs and a set of actions. The selection of appropriate connections between inputs and actions was moulded by the process of evolution. It is notable that the agents in our simulations evolved many of the strategies that were postulated by previous researchers. Thus, in the absence of phenotypic markers, three distinct strategies emerged corresponding to the dove, the hawk and the bourgeois. This shows that our results are not in opposition to game theory, but represent an extension of previous approaches. In the presence of markers, the evolution resulted in some predictable modifications of these basic strategies, but also in the emergence of a new one. Cooperative doves avoided competition with in-group members, whereas cooperative hawks – ‘ravens’ – avoided attack on phenotypically similar agents. The new strategy was the starlings, who lived in groups and defended territory cooperatively against predation. (Bolding added)

The bolded sentences are important. There was no front-loading of strategies from which critters could choose. It was not necessary to surreptitiously smuggle complex behaviors into the model’s code. ID creationists kick and scream about that, but it isn’t necessary. Evolutionary processes can produce complex behaviors, as they produce complex structures, by modifying and elaborating very minimal initial conditions. Complexity ain’t hard at all to evolve, and novelty emerges as a natural consequence of evolution.

RBH

47 Comments

That is indeed a fantastic study. I think the most important message is the predictive value this type of analysis can have with respect to varying survival strategies in the wild, as environmental conditions change.

It is often claimed by Creationists that Darwinian mechanisms preclude the appearance of any altruistic/cooperative behavior, but in fact there is extensive theoretical and field work that highlight the situations in which such strategies can result in a net increase in fitness for the carriers.

Also, a model for the evolution of altruistic/cooperative behavior you forgot to mention is the “green beard” model, in which genes affecting altruism/cooperation are phenotypically detectable (either directly of via closely associated genetic loci) because they are reflected in traits that are physically distinguishable, and allow the direct identification of carriers. A striking confirmation of this model in side-blotched lizards was reported just a few days ago in PNAS, and was described by John Lynch here.

Yeah, I thought about mentioning the green beard effect, but ran out of steam.

this is not the only animal where these types of reproductive strategies have been observed.

for example the behavior of the orange-throated males is analagous to “piracy”, first observed in fish (of course :) ), and further studies have since elucidated stable varying reproductive strategies in various populations, including cooperation, sneaking, and piracy, all within the same populations.

I first heard about this in a species of wrasse (a species of Thallasoma, IIRC), off of St. Croix (Virgin islands) in 1987. The study was published in Nature in 87 or 88 by a friend of mine, Eric Van Den Berghe.

since then, many other species have been studied that exhibit similar apparently stable patterns of territorial/reproductive strategy.

see for example work done by Taborsky (still with wrasses, interestingly):

Taborsky, M. (1994). Sneakers, satellites, and helpers: Parasitic and cooperative behavior in fish reproduction. Advances in the Study of Behavior, 23, 1-101.

Taborsky, M. (2001). The evolution of bourgeois, parasitic, and cooperative reproductive behaviors in fishes. Journal of Heredity, 92, 100-110.

Taborsky, M., Hudde, B., & Wirtz, P. (1987). Reproductive behaviour and ecology of Symphodus (Crenilabrus) ocellatus, a European wrasse with four types of male behaviour, Behaviour, 102, 82-118.

Also, I’m sure you will find Dr. Robert Warner at the University of CA, Santa Barbara to be an fountain of information on this subject.

of course the point is, the range of organisms that have now been shown to exhibit stable but widely varying reproductive strategies within a given population should further put to rest doubts about the role of selection in shaping behavior.

In fact, the very elegance and surprising results of the initial studies on the reproductive strategies in wrasses were instrumental in influencing my choice to study behavioral ecology and evolutionary ethology as a grad student.

this stuff is just… great!

Has anyone got anthing on how the church mouse evolved ?

The bolded sentences are important. There was no front-loading of strategies from which critters could choose. It was not necessary to surreptitiously smuggle complex behaviors into the model’s code. ID creationists kick and scream about that, but it isn’t necessary. Evolutionary processes can produce complex behaviors, as they produce complex structures, by modifying and elaborating very minimal initial conditions. Complexity ain’t hard at all to evolve, and novelty emerges as a natural consequence of evolution.

RBH

[salvador] Ah, but the simulation ran on a computer chip, which is the product of Intelligent Design! Obviously the Complex Specified Information was injected into the chip at the factory in Santa Clara. [/salvador]

RBH: Great write-up. The obvious question came to mind: Is this work applicable to the human condition? You answered that by pointing to Axelrod’s work, so thanks for the pointer. I’ve been reading up on Hofstede et al work on cultural dimensions; now I’m curious to see if there is any correlation between the concept of cultural dimensions and Axelrod’s work. If any readers know of such correlation, please share.

Fascinating study and post, but your description is incomplete (I know your focus is on evolution, but I’m a programmer and gamer and and find this type of simulation fascinating).

You say:

“Initially the critters have just three “pre-wired” actions available to them: move into the forward cell if ‘food’ is there; eat if ‘food’ is in the current cell; and divide otherwise.”

But were there other actions possible (turning, waiting). How did they attack? And was hunger a built-in or variable trait?

rcriii asked

But were there other actions possible (turning, waiting). How did they attack? And was hunger a built-in or variable trait?

Other behaviors were “possible” in the sense that the neural net connecting receptors to effectors could make the appropriate connections if the appropriate mutations in the weight matrix occur and if there is some selective advantage to the steps so cumulative selection can kick in. The authors did not follow (or at least didn’t report following) lineages through time to trace the trajectory of the evolution of the strategies, so more I cannot say. That to me would be an obvious refinement, on the order of the lineage tracing done in the Lenski, et al. paper I linked above.

Critters attacked by “eating” another critter in the current cell, thereby obtaining the prey critter’s internal resources. Predation – hunting – involved moving to a cell sensed to have another critter and then eating it.

The Nature paper and an earlier paper by Burtsev are not clear at all about how hunger operates. I assume, but do not know, that a critter can die from depletion of internal resources, but the papers are opaque on that aspect of the model.

RBH

Hopefully completely ignorant questions can be taken here. Do I have this right? So, presumably, those critters that attack others with their own string barcode become extinct, but how does the program develop the programming code that allows the critter to selectively attack only non-self? Is that variable randomly generated, added to the program, and then selected for? So the discrimination part of the study is some line initially in the program that says “read barcode of neighboring critter”?

Should be some better term than “cell”. Why not “territory”?

Richard, I don’t see how this study, nor any of the other computer simulations to which you refer, including the much discussed Lenski et.al. Avida study, demonstate anything about evolution. What is perfectly clear is that none of these programs would demonstrate a thing without being programmed (i.e. designed) in the first place. Whatever parameters are designed into these programs, they assumes evolutionary processes in the first place, which is begging the question, thus making these studies biologically irrelevant. Look at what Burtsev and Turchin write: “Our model did not endow agents with a set of preconceived strategies — all that we assumed was that agents have a set of elementary sensory inputs and a set of actions. The selection of appropriate connections between inputs and actions was moulded by the process of evolution.” To which you respond “There was no front-loading of strategies from which critters could choose. It was not necessary to surreptitiously smuggle complex behaviors into the model’s code. ID creationists kick and scream about that, but it isn’t necessary. Evolutionary processes can produce complex behaviors, as they produce complex structures, by modifying and elaborating very minimal initial conditions. Complexity ain’t hard at all to evolve, and novelty emerges as a natural consequence of evolution.”

THose minimal initial conditions to which you refer are anything but minimal. They require an imparting of information by an intelligent agent into the system, without which nothing would happen at all. Where did all that information (i.e. the computer program itself, all algorithms included) come from in the first place, if not an intelligent agent? For all you can tell the outcomes are the result of the information laden “minimal” initial conditions. Unless and until you can explain the evolutionary origin of all that initial information, ascribing all the outcomes to evolutionary processes is a sophisticated excercise in begging the question. They could just as easily be the outcome of the designed initial conditions.

Neat result; should be a fun read. I am surprised that it only took a single layer in the neural net to produce these behaviors, though. Even bacteria have more complex behavioral wiring than that.

Look like DonaldM gave the response predicted by steve s. But if the way to “falsify” ID is to show that evolutionary forces can generate complex specified irreducible whatever, but the only way to do that is to design systems in which evolutionary forces can act which necessarily makes them ‘designed’ because human intelligence was involved somewhere in the process, then there is no possible way to us actually to apply the necessary tests or experiments. Anything researchers do will be tainted with intelligence, therefore subject to that particular ID complaint.

One more reason why ID is not falsifiable science.

Donald M, do you doubt the utility of computer simulations in other fields, like, say, engineering, or meteorology? If not, why not? Everything you say here could as easily be grounds for rejecting the results of any such simulation as “the outcome of designed initial conditions.”

What is perfectly clear is that none of these programs would demonstrate a thing without being programmed (i.e. designed) in the first place. Whatever parameters are designed into these programs, they assumes evolutionary processes in the first place, which is begging the question, thus making these studies biologically irrelevant.

All they assume is that you have imperfect self-replication and selective pressures. The rest arises from the simulation. There’s no big red button labelled “evolve stuff” that you have to press to get these effects. They’re built into the whole idea of reproduction. Differential reproduction due to heritable variation = evolution => cool effects.

This sort of thing is fairly common in mathematics, unless you fancy arguing that Mandelbrot already knew what his famous fractal would look like and merely selected the generator algorithm on the basis of that*…

* This would be ludicrous. Don’t bother.

This would be ludicrous. Don’t bother.

You don’t really expect such a warning to deter rather than encourage a creationist, do you?

Donald is conflating two different ID arguments, with the usual ID nonchalance about truth, justice, and the American way.

The first is the usual IDiocy: the principal pillars of evolution, random mutation and natural selection (hereafter the “Forces of Evolution”), cannot produce (insert whatever results ID is blithering on about this week–in our case, the “altruistic” strategies of organisms–although Donald gratuitously throws in “new information” as a makeweight and diversion).

The second is the claim that unaided naturalistic forces cannot generate living replicants in the first place, for the Forces of Evolution to operate on ever after.

Here, Donald overlaps the two, claiming that, if the scientists have to “program in” the Forces of Evolution in the first place, then the whole exercise is question-begging, circular bogus-osity, even if the resulting altruistic strategies were not programmed in.

Good attempt at circumlocution, Donald, but it should now be quite obvious to the rest of us that you have just conceded that, given the existence of replicating entities upon whom the Forces of Evolution can operate, altruistic strategies can be generated without the further intervention of purpose, intelligence, or design.

Since “altruistic strategies” will certainly also count as “new information” to any halfway reasonable reader, Donald has just given away the game as to argument # 1–presumably without “iintending” to do so. Not that we really needed Donald M’s grudging (albeit unwitting) “agreement” in the first place.

Maybe it’s time that the programmers got to work on Problem No. 2. Let’s simulate some simple organic molecules jostling around in a variety of plausible early-Earth environments, and see if we can generate “reaction products” that begin to replicate…

Look like DonaldM gave the response predicted by steve s.

You can sometimes tell what’s coming. There’s only about 400 claims they repeat without understanding. I haven’t seen a new one all year.

Mike asked

So, presumably, those critters that attack others with their own string barcode become extinct, but how does the program develop the programming code that allows the critter to selectively attack only non-self? Is that variable randomly generated, added to the program, and then selected for? So the discrimination part of the study is some line initially in the program that says “read barcode of neighboring critter”?

The difference between a critter’s own “barcode” and that of other critters in its field of view is an input to a critter – an input to the neural net.

The input vector I is populated with information about the presence of resource and other agents in the field of vision (the cell where the agent is, the neighbour cell in front of the agent, and the cells on the right and left), the level of internal resource and the euclidean distance between marker vectors of the agent and its partner for potential interaction. (p. 1043)

So a value – the Euclidean distance between self’s barcode and other’s barcode – is available. That’s more or less equivalent to the critters having the ability to discriminate shades of grey, but not having any initial behavioral links to that discrimination – their sensory system can tell light from dark but they don’t (initially) do anything as a consequence. They have the sensory capacity to make the discrimination between self and other, but behavioral consequences of the discrimination, if any, must evolve de novo. The “code” that evolves is weights in the neural net connecting inputs to outputs/behaviors. The weights associated with the “barcode” different are initially set to zero.

And recall that critters with similar (or identical) bar codes are likely to be kin – barcodes are inherited.

Mike asked

Should be some better term than “cell”. Why not “territory”?

“Cell” on a grid is from the math side of the house.

J.G. Cox remarked that

I am surprised that it only took a single layer in the neural net to produce these behaviors, though. Even bacteria have more complex behavioral wiring than that.

Don’t underestimate single layer nets. Perceptrons had a pretty good run in the late 1950s and 1960s until Minsky & Papert (IMO unfairly) trashed them, setting back NN research 10 years or more. Who cares if a pattern recognition net can’t learn an exclusive OR? Humans have a tough time doing it, too!

I’ll get to DonaldM later this evening or over the weekend. I’ll say here only that his position would imply (as he may believe) that since computer hurricane simulations are intelligently designed so are hurricanes, and Pat Robertson was right after all.

RBH

DonaldM Wrote:

What is perfectly clear is that none of these programs would demonstrate a thing without being programmed (i.e. designed) in the first place. Whatever parameters are designed into these programs, they assumes evolutionary processes in the first place, which is begging the question, thus making these studies biologically irrelevant.

By your logic …

Engineer tests a proposed aircraft design using fluid dynamics models, etc etc. The various models show that the airplane will fly.

Engineer builds airplane.

Engineer flies airplane.

Earth’s atmosphere was intelligently designed. QED.

Nice work!

Are scientists defending evolution starlings, ravens or hawks?

Gee, Donald is it that time of the month already? Time for another drive-by? Will Heddle and Sal and all the others be following shortly?

Hey, the last dozen or so times you did your monthly drive-by, you neglected to answer a few simple questions for me. …

Here, Donald, let me repeat my questions for you once more, just in case you missed them the first dozen times:

What, again, did you say the scientific theory of ID is? How, again, did you say this scientific theory of ID explains these problems? What, again, did you say the designer did? What mechanisms, again, did you say it used to do whatever the heck you think it did? Where, again, did you say we can see the designer using these mechanisms to do … well . . anything?

Or is “POOF!! God — uh, I mean, The Unknown Intelligent Designer — dunnit!!!!” the extent of your, uh, scientific theory of ID .… ?

How does “evolution can’t explain X Y or Z, therefore goddidit” differ from plain old ordinary run-of-the-mill “god of the gaps”?

Here’s *another* question for you to not answer, Donald: Suppose in ten years, we DO come up with a specific mutation by mutation explanation for how X Y or Z appeared. What then? Does that mean (1) the designer USED to produce those things, but stopped all of a sudden when we came up with another mechanisms? or (2) the designer was using that mechanism the entire time, or (3) there never was any designer there to begin with.

Which is it, Donald? 1, 2 or 3?

Oh, and if ID isn’t about religion, Donald, then why do you spend so much time bitching and moaning about “philosophical materialism”?

(sound of crickets chirping)

You are a liar, Donald. A bare, bald-faced, deceptive, deceitful, deliberate liar, with malice aforethought. Still.

DonaldM Wrote:

I don’t see how this study, nor any of the other computer simulations to which you refer, including the much discussed Lenski et.al. Avida study, demonstate anything about evolution. What is perfectly clear is that none of these programs would demonstrate a thing without being programmed (i.e. designed) in the first place.

And Galileo’s spheres wouldn’t have gone anywhere if he hadn’t designed a bunch of ramps and placing them at the top, thus totally stacking the deck in favor of their rolling downwards. Therefore, gravity is an atheist lie.

Donald: “What is perfectly clear is that none of these programs would demonstrate a thing without being programmed (i.e. designed) in the first place. Whatever parameters are designed into these programs, they assumes evolutionary processes in the first place, which is begging the question, thus making these studies biologically irrelevant. Look at what Burtsev and Turchin write: “Our model did not endow agents with a set of preconceived strategies — all that we assumed was that agents have a set of elementary sensory inputs and a set of actions. The selection of appropriate connections between inputs and actions was moulded by the process of evolution.” “

You need to go back to Darwin for the origion of “evolutionary processes” Time for Darwin’s summary of natural selection:

“If, during the long course of ages and under varying conditions of life, organic beings vary at all in the several parts of their organization, and I think this cannot be disputed; if there be, owing to the high geometric powers of increase of each species, at some age, season, or year, a severe struggle for life, and this certainly cannot be disputed; then, considering the infinite complexity of the relations of all organic beings to each other and to their conditions of existence, causing an infinite diversity in structure, constitution, and habits, to be advantageous to them, I think it would be a most extraordinary fact if no variation ever had occurred useful to each beings welfare, in the same way as so many variations have occured useful to man. But if variations useful to any organic being do occur, assuredly individuals thus characterized will have the best chance of being preserved in the struggle for life; and from the strong principle of inheritance they will will tend to produce offspring similarly characterized. This principle of preservation, I have called, for the sake of brevity, Natural Selection.” [Origin, p 127 6th ed.]

Now, look at that carefully. It is a syllogism. Major premise: organisms vary. Minor premise: geometric increase in population results in struggle for existence. Conclusion: Variations (designs) useful in the struggle will be preserved.

This is what Donald calls “assume evolutionary processes” But it’s not an assumption, but a CONCLUSION from demonstrated biological conditions.

What we have here is an unintelligent process that gives design. Donald has 2 possible choices to refute the unintelligent process: 1) argue that one of the premises is wrong. That is futile as they are amply documented. 2) Argue that the conclusion doesn’t follow. That also is futile. It’s obvious. So, without intelligent input, the result is design. The computer program simply set up the two premises.

Donald’s other argument is the origin of the “elementary sensory inputs and a set of actions”. However, these come from chemistry. Sensory inputs are interactions between molecules and receptors. Actions are the result of the receptors with other molecules. Both are inherent in chemical reactions. Again, no intelligent input required.

Anton Mates and Paul Lucas took care of DonaldM, so I won’t bother. Thanks!

RBH

J.G. Cox wrties:

Look like DonaldM gave the response predicted by steve s. But if the way to “falsify” ID is to show that evolutionary forces can generate complex specified irreducible whatever, but the only way to do that is to design systems in which evolutionary forces can act which necessarily makes them ‘designed’ because human intelligence was involved somewhere in the process, then there is no possible way to us actually to apply the necessary tests or experiments. Anything researchers do will be tainted with intelligence, therefore subject to that particular ID complaint.

Saying this a “particular ID complaint” mischaracterizes the nature of comment. The “complaint” as you put it doesn’t really have all that much to do with ID and whole to do with the rules of logic and reason that nearly everyone (supposedly) accepts. One of theose rules says that it is a logical fallacy to assume the consequent in making an argument. In common terms that is begging the question. That is the problem with using these computer models because the intelligent agents must program in the assumed parameters within which the program operates and then further assume that whatever output results maps to biological reality. This is precisely the points at issue. Furthermore is it assumed that the imparting of information from intelligent agents into the computer system in order to run the simulations doesn’t map to biological reality, but the outputs produced thereby do. What’s the scientific basis for that assumption…that no information was imparted into the biological system from an intelligent source as well?

To claim that the output of such simulations map to biological reality but the “minimal initial” conditions established by the imparting of information from intelligent agents (i.e. programmers) does not is to make a huge assumption and sets up a question begging arrangement. Hence my “complaint”, as you put it. It’s a sophisticated excercise in begging the question.

ah DonaldM. you said. It’s a sophisticated excercise[sic] in begging the question. is an unsophisticated oxymoron. Moron. http://www.drury.edu/ess/Logic/Info[…]uestion.html

DonaldM wrote

One of theose rules says that it is a logical fallacy to assume the consequent in making an argument. In common terms that is begging the question. That is the problem with using these computer models because the intelligent agents must program in the assumed parameters within which the program operates and then further assume that whatever output results maps to biological reality. This is precisely the points at issue.

The “assumed parameters” are those identified by theory, and the models ask the question “Do these assumed parameters, when their values are in the range hypothesized, in fact produce the kinds of outcomes theory predicts?” That is, the models allow asking the question. If the models did not have the capability of embodying the parameter values identified by the theory, they could not serve as test beds for the theory. Note that in testing, one varies parameter values. For example, in the study at issue, the value of variable “information to allow discriminating similar from dissimilar critters available” was varied – the two conditions I wrote of in the OP. That’s how one conducts experiments: by varying the values of variables to ascertain whether one’s theory has identified the relevant variables and whether the behavior of the model matches the predictions of theory.

And specifically what are the assumed parameters that were “program[med] in”? That replicators with heritable variation exist in a context in which resources are limited; that the replicators have sensory apparatus capable of sensing minimal information about their surroundings and their own internal state; that they can perform very basic behaviors for individual survival (movement forward and eating); and that during replication (division) occasional random mutations in their cognitive ‘genes’ occur. What else, DonaldM?

DonaldM wrote

Furthermore is it assumed that the imparting of information from intelligent agents into the computer system in order to run the simulations doesn’t map to biological reality, but the outputs produced thereby do. What’s the scientific basis for that assumption…that no information was imparted into the biological system from an intelligent source as well?

DonaldM should specifically identify the “information” from intelligent agents that produced the outputs, which in the present case are the different strategies for interactions of agents. Merely saying “information” is, well, uninformative. Precisely what information was imparted that somehow invalidates the model?

DonaldM wrote

To claim that the output of such simulations map to biological reality but the “minimal initial” conditions established by the imparting of information from intelligent agents (i.e. programmers) does not is to make a huge assumption and sets up a question begging arrangement. Hence my “complaint”, as you put it. It’s a sophisticated excercise in begging the question.

In fact, no one has claimed that the initial conditions were not inserted by programmers. They were. That’s how one does any experiment: one intelligently sets up initial conditions and manipulates variables to see what happens. The question DonaldM must answer is whether those minimal initial conditions somehow produce the outputs because intelligent programmers wrote them. The minimal initial conditions were replicators with sensors and an effector apparatus connected by a simple cognitive apparatus (single layer neural net), replicating in an environment with limited resources. Intervening between the initial conditions and the outcomes are purely evolutionary processes – mutations and replication. For his objection to hold water, DonaldM has to show that the fact that an intelligence created those initial conditions must lead inescapably to the outcomes, independent of the operation of the evolutionary processes that intervene between initial conditions and outcomes. He must show just what about those initial conditions (a) is necessary and (b) does not occur in nature. Otherwise his objections are just so much noise in the system.

RBH

DonaldM Wrote:

Saying this a “particular ID complaint” mischaracterizes the nature of comment. The “complaint” as you put it doesn’t really have all that much to do with ID and whole to do with the rules of logic and reason that nearly everyone (supposedly) accepts.

This is quite true. Your objection, if valid, would rule out any sort of experimental science, whether related to evolution or not, since all human experimenters are intelligent agents.

What’s the scientific basis for that assumption…that no information was imparted into the biological system from an intelligent source as well?

There is no such assumption. It’s an empirical observation that the model’s creators did not design or even anticipate the behaviors which appeared in the model. Whether they nonetheless unknowingly imparted the necessary “information” for such behaviors, by building the model in the first place and setting its initial conditions, is irrelevant. Evolutionary theory does not deny that intelligent agents could have been responsible for the creation of the universe.

C.J. O’Brien writes:

Donald M, do you doubt the utility of computer simulations in other fields, like, say, engineering, or meteorology? If not, why not? Everything you say here could as easily be grounds for rejecting the results of any such simulation as “the outcome of designed initial conditions.”

Fair question and the answer is of coure not. The difference is that weather and engineering models aren’t trying to make a case for or against undirected natural causes as being sufficient to explain some oberved phenomenon. That is the entire focus of the models being discussed here. Clearly this study and the Avida study to which Richard referred in the OP are meant to show that undirected natural causes are sufficient to explain ‘X’. That isn’t the case in most other sciences that use computer models.

It is also interesting to note that studies like the ones mentioned here give the lie to the “ID isn’t science because it isn’t testable or falsifiable” mantra. Clearly these computer models are intended to show that no ID is necessary. In effect, these studies are intended to falsify, and thereby test, ID concepts. Richard says so himself in the OP: “Evolutionary processes can produce complex behaviors, as they produce complex structures, by modifying and elaborating very minimal initial conditions. Complexity ain’t hard at all to evolve, and novelty emerges as a natural consequence of evolution.” Apparently, according to Richard, this is a test of the origination of CSI, among other things.

Fair question and the answer is of coure not. The difference is that weather and engineering models aren’t trying to make a case for or against undirected natural causes as being sufficient to explain some oberved phenomenon. That is the entire focus of the models being discussed here.

Supposing that were true, what difference would it make to the soundness of the approach?

And no, weather and engineering models aren’t trying to make a case for or against “undirected natural causes as being sufficient to explain some observed phenomenon”, because, as with evolution, we “assume” that only so-called “natural causes” are acting in the absence of evidence for any “other kind”.

The point of computer weather models is to hone them to the point where they can predict weather accurately a few days out. Likewise with genetic algorithms, competent people don’t question that evolution happened according to “natural causes”, the point is to show how it occurred, what mechanisms produce the observed results, etc. Or some simply use evolutionary methods to produce desired results.

DonaldM has the absurd belief that we’re trying to show that natural causes could produce the life we see. That would be a bizarre task in science. To see which “natural causes” are responsible for evolution is important, on the other hand.

I’m sure that others have noticed how strange the IDist/creationist approach to evolution is. Each step forward they misconstrue as being an attempt to “prove evolution”, not as what it is, an increase in knowledge of how evolution happened according to known mechanisms. A few seem a bit more sophisticated, but anyone who has read Dembski knows that this “leading light of ID” regularly implies that research is simply trying to bolster the concept that evolution happened by known means. Their followers suck it up, come onto forums, and generally show how little they know.

It comes in handy to believe that research is trying to show that evolution could occur, because any gap in the results can be misconstrued into a “failure of evolutionary theory”.

No, we know that evolution occurred, and almost certainly via RM + NS (&tc.) because of the evidence, because “microevolution” and “macroevolution” produce essentially the same cladistic patterns and similar genetic changes (though macroevolution is sometimes considered (or defined) to involve larger changes than the familiar point mutations important in microevolution).

Computer simulations are used to model the evolution that we know occurred, apparently without intervention (none seen in the geological record, nor in genomes) to learn which mechanisms are most important, and what they are important for. We care not a fig for showing that weather and evolution are “natural” (except when pseudoscience raises its ugly head), we’re only interested in how it proceeds.

So another creationist who fails to comprehend what’s at stake in science. To be sure, if the various creationists (including IDists) did comprehend, there wouldn’t be much chance that they’d be creationist.

Glen D http://tinyurl.com/b8ykm

Hey Donald, are you going to answer my questions?

(sound of crickets chirping)

Thought not.

Isn’t it time for you to drive off now, Donald?

Heddle is waiting for you to get out of his lane.

The difference is that weather and engineering models aren’t trying to make a case for or against undirected natural causes as being sufficient to explain some oberved phenomenon.

WHAT????!!!????? You mean science isn’t “materialistic”?

Do please show us the difference, Donnie. What, precisely, about “evolution” is any more “materialistic” than, say, weather forecasting or accident investigation or medicine. Please be as specific as possible.

I have never, in all my life, ever heard any weather forecaster mention “god” or “divine will” or any “supernatural” anything, at all. Ever. Does this mean, in your view, that weather forecasting is atheistic (oops, I mean, “materialistic” and “naturalistic” —- we don’t want any judges to think ID’s railing against “materialism” has any RELIGIOUS purpose, do we)?

I have yet, in all my 45 years of living, to ever hear any accident investigator declare solemnly at the scene of an airplane crash, “We can’t explain how it happened, so an Unknown Intelligent Being must have dunnit.” I have never yet heard an accident investigator say that “this crash has no materialistic causes — it must have been the Will of Allah”. Does this mean, in your view, that accident investigation is atheistic (oops, sorry, I meant to say “materialistic” and “naturalistic” — we don’t want any judges to know that it is “atheism” we are actually waging a religious crusade against, do we)?

How about medicine. When you get sick, do you ask your doctor to abandon his “materialistic biases” and to investigate possible “supernatural” or “non-materialistic” causes for your disease? Or do you ask your doctor to cure your naturalistic materialistic diseases by using naturalistic materialistic antibiotics to kill your naturalistic materialistic germs?

Since it seems to me as if weather forecasting, accident investigation, and medicine are every bit, in every sense,just as utterly completely totally absolutely one-thousand-percent “materialistic” as evolutionary biology is, why, specifically, is it just evolutionary biology that gets your panties all in a bunch? Why aren’t you and your fellow Wedge-ites out there fighting the good fight against godless materialistic naturalistic weather forecasting, or medicine, or accident investigation?

Or does that all come LATER, as part of, uh, “renewing our culture” .… . ?

And on the other hand, engineers use computer programs clearly modeled after biological processes to produce efficient artifacts. The computer programs are called (1) evolutionary algorithms and (2) computer swarm intelligence. Evolutionary algorithms are used to evolve efficient X-band antennas as well as both analog and digital circuits. Computer swarm algorithms, of which some are called ‘ant colony’ algorithms, are used more often to solve network optimization problems.

No matter which style, there is a form of random selection and weed-out via a fitness function. Indirectly, this looks to be a further verification of the power of evolution to create novelty.

Donald wants to argue that evolution doesn’t work, but in effect just complains that it does work.

Re “One of those rules says that it is a logical fallacy to assume the consequent in making an argument. In common terms that is begging the question. That is the problem with using these computer models because the intelligent agents must program in the assumed parameters within which the program operates and then further assume that whatever output results maps to biological reality.”

The fallacy mentioned here applies to deductive argument, not to using experiments to do empirical testing of a prediction. An empirical test is not a deductive argument, therefore the objection does not apply.

Henry

DonaldM wrote

The difference is that weather and engineering models aren’t trying to make a case for or against undirected natural causes as being sufficient to explain some oberved phenomenon. That is the entire focus of the models being discussed here.

And that’s bullshit. The models being discussed here are directed at learning about the conditions and variables in which various phenomena occur. That’s what scientists do, as distinguished from armchair apologists.

DonaldM wrote furter

It is also interesting to note that studies like the ones mentioned here give the lie to the “ID isn’t science because it isn’t testable or falsifiable” mantra. Clearly these computer models are intended to show that no ID is necessary. In effect, these studies are intended to falsify, and thereby test, ID concepts. Richard says so himself in the OP: “Evolutionary processes can produce complex behaviors, as they produce complex structures, by modifying and elaborating very minimal initial conditions. Complexity ain’t hard at all to evolve, and novelty emerges as a natural consequence of evolution.” Apparently, according to Richard, this is a test of the origination of CSI, among other things.

Had I meant to say this was a “test of the origination of CSI” I’d have said so. CSI is a vacuous notion – were it not, we’d have publications describing how it is measured and providing validation and reliability data for it. Since not even its originator, Dembski, has bothered to do any of that it’s vacuous. One can’t test the origination of something one can’t detect.

The studies employing computer models are indifferent to ID – ID isn’t ‘testable’ because it proposes nothing that one can test. All it claims is that evolution can’t do this or that, and the results from these and other studies demonstrate that’s a false claim. And for sure the models under discussion aren’t “tests” of ID. They’re explorations of the power of evolutionary processes to produce the phenomena we see. That they happen to exclude non-material interference and puffs of smoke as variables is because they’re works in science, not apologetics.

RBH

I should add that I’m still waiting for DonaldM’s identification of the “information” from intelligent agents that produced the outputs, which in the present case are the different strategies for interactions of agents. Merely saying “information” is, well, uninformative. Precisely what information was imparted that somehow invalidates the model?

RBH

Donaldm Wrote:

It is also interesting to note that studies like the ones mentioned here give the lie to the “ID isn’t science because it isn’t testable or falsifiable” mantra. Clearly these computer models are intended to show that no ID is necessary. In effect, these studies are intended to falsify, and thereby test,

First of all none of this falsifies ID, as ID remains a logical possibility even if it can be shown that natural processes can explain X. This is a common confusion amongst ID apologetics. Secondly, ID is not as much non-science as it is scientifically vacuous. ID is only testable to the extent that it claims that X cannot be explained by natural processes, but that is not really the ID DonaldM has in mind now is it… He believes that somehow the absence of such identified processes is somehow evidence of ID. There is so much wrong with ID’s case, whether it be based on ‘logic’ or ‘science’ it can be easily shown to be without any merrit, scientifically vacuous and theologically dangerous. DonaldM’s contributions are a good example of ID “in-action”

Another exploration of the evolution of cooperation

A new route to the evolution of cooperation.

Santos FC, Pacheco JM. J Evol Biol. 2006 May;19(3):726-33.

IRIDIA, Universite Libre de Bruxelles, Brussels, Belgium.

The Prisoner’s Dilemma (PD) constitutes a widely used metaphor to investigate problems related to the evolution of cooperation. Whenever evolution takes place in well-mixed populations engaged in single rounds of the PD, cooperators cannot resist invasion by defectors, a feature, which is somewhat alleviated whenever populations are spatially distributed. In both cases the populations are characterized by a homogeneous pattern of connectivity, in which every individual is equivalent, sharing the same number of neighbours. Recently, compelling evidence has been accumulated on the strong heterogeneous nature of the network of contacts between individuals in populations. Here we describe the networks of contacts in terms of graphs and show that heterogeneity provides a new mechanism for cooperation to survive. Specifically, we show that cooperators are capable of exploring the heterogeneity of the population structure to become evolutionary competitive. As a result, cooperation becomes the dominating trait in scale-free networks of contacts in which the few highly connected individuals are directly inter-connected, in this way contributing to self-sustain cooperation.

DonaldM Wrote:

The difference is that weather and engineering models aren’t trying to make a case for or against undirected natural causes as being sufficient to explain some oberved phenomenon.

Really? So when meteorologists model, say, the formation of hurricanes, they periodically invoke Vayu or Marduk to set up the air currents and temperature distributions just right?

When engineers model the collapse of a building under excessive load, do they run two models, one with gremlins and one without?

Which science’s computer models treat the possibility of directed supernatural causes differently than this study did?

I think that said that small groups with internal cooperation are more advantageous for their members than are groups that don’t have internal cooperation?

Henry

Uh, I was referring to the post

Pete Dunkelberg on May 6, 2006 10:11 PM” Another exploration of the evolution of cooperation A new route to the evolution of cooperation. […]

I wrote an artifical life program last month that has “bugs” controlled by neural nets. Bugs can sense food pellets, the edges of the world, and other bugs.

The simulation starts out with the weights of the synapses in the neural nets completely randomized. Sometimes, one or two bugs will just happen to move more or less in a straight line and collect enough food to reproduce. And once they get a foothold, they just keep getting better.

When a bug reproduces, its offspring is made by copying the parent bug data structure and then changing the weight of one randomly selected synapse to a new random value.

Let it run for a few hours, and interesting behaviors develop. Follow the link for details.

That’s a neat demonstration, Walter. Watching the evolution of a system like that is entrancing. I especially like the speciation you saw. That third species appears to be a nice illustration of speciation following geographic isolation. I’m currently doing ‘DNA’ analyses of the ‘species’ my company’s GAs generate, with an applied goal in mind of course – we make our living by hiring out the products of our GAs – but it’s still entrancing from a theoretical point of view.

RBH

A natural prediction of ID: all those meterologists have daily revelations filled with atmospheric Information direct from God.

This article has been linked to and discussed on MetaFilter.

Initially the critters have just three “pre-wired” actions available to them: move into the forward cell if ‘food’ is there; eat if ‘food’ is in the current cell; and divide otherwise. Every action (except eating) depletes the critter’s internal resource, which must be replenished by eating.

Eating depletes the critter’s internal store if there is no “food” item in the cell. But if the food is present and eating is executed then agent’s internal store has a positive balance of resource.

There was no front-loading of strategies from which critters could choose.

This is incorrect as well. I don’t think front-loaders posit the predetermination of strategies.

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This page contains a single entry by Richard B. Hoppe published on May 4, 2006 7:40 PM.

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