Russ, et. al, I should send an email focusing on group selection, but instead I will point out, on a very related note, that there was a pretty nice altruism article published by some of the people on the list not too long ago ;- ) <http://jasss.soc.surrey.ac.uk/9/2/4.html> -- That article demonstrates that a strategy that always co-operates, but changes partners if faced with a defector, out performs strategies that only co-operate under certain circumstances (e.g., the much revered tit-for-tat). At least one of the authors knows Wilson pretty darn well, and another got to present the paper in a symposium with Wilson and got pretty good compliments.
I had a fantasy about creating a genetic algorithms version of the same program, but got side tracked on other projects. The idea was that we would start with a population of all non-co-operators non-leavers. Each would have a "chromosome" where there was a low probability it would "mutate", gaining or losing whichever ability the gene represented. Presumably it would take many, many generations for co-operation to emerge as a contender in the population. Given a limited number of generations, most populations would be unlikely to evolve altruism (i.e., the occasional mutation would be quickly eliminated). However, the interesting study would be too look back at those populations in which altruism DID evolved, and determine the order of events. Our hypothesis, based on the prior simulation (and the really good logic behind it) would be that leaving evolves first, then co-operation. At least, that would be the typical pattern. It would be a really fun study, and I would be happy to help put it together. It would be done already except for two factors 1) a dispersion of the interested parties and 2) new Netlogo versions required tweaking the original program more than the remaining brain-power allowed. The last version was pretty heavily documented (admittedly by people who are not skilled at the art), so it shouldn't take a skilled programer too long to fix it up. Anyway, already a longer email than intended, Eric P.S. Nick knows the group selection stuff backwards and forwards. I can do pretty good schpeel too, and you should scold me for not having answered your question more exactly. The reason this is related is because group selection is only an interesting conversation (i.e., only a controversial conversation) if you are trying to use it to explain the evolution of altruism. On Tue, Mar 9, 2010 08:52 PM, Russ Abbott <[email protected]> wrote: >>David Sloan Wilson has been an advocate of <http://www.nbb.cornell.edu/wkoenig/wicker/NB4340/Wilson&Wilson2008.pdf> in evolution for quite a while. (And I think he's right.) What I'd like to know is whether anyone knows of any work on group selection in a (computational) genetic algorithm context. > >Suppose I wanted to evolve a fleet of cars for a car rental agency. One approach would be a genetic algorithm in which the population elements were fleets, each of which is a collection of cars. Crossover would generate children fleets some of whose cars were copied from each parent. > >In addition, I want to assume that the car properties themselves are evolvable. So one could, for example, crossover two cars to produce offspring cars with properties from the two parents. > >This has also been called multi-level selection because evolution takes place at multiple levels at once: in this case at the fleet level and at the car level simultaneously > >Is anyone aware of a framework that supports this sort of process? Or is anyone aware of any papers that describe results in this area? > >Thanks. > >-- Russ > > > > >-- Russ Abbott > >______________________________________ > > Professor, Computer Science > California State University, Los Angeles > > cell: 310-621-3805 > blog: <http://russabbott.blogspot.com/> > vita: <http://sites.google.com/site/russabbott/> > > >______________________________________ > > > ============================================================ >FRIAM Applied Complexity Group listserv >Meets Fridays 9a-11:30 at cafe at St. John's College >lectures, archives, unsubscribe, maps at http://www.friam.org > Eric Charles Professional Student and Assistant Professor of Psychology Penn State University Altoona, PA 16601
============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
