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  Topic: Evolutionary Computation, Stuff that drives AEs nuts< Next Oldest | Next Newest >  

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Joined: Sep. 2006

(Permalink) Posted: June 18 2009,21:42   

Quote (Steve Schaffner @ June 18 2009,20:53)

Basically, he is applying reductions in heritability twice. The heritability function itself, and then this random procedure for selecting reproductive winners by re-ranking them before truncation and passing to the next generation. We could modify the divisor to some function(randomnum) and adjust the degree and type of randomness for picking winners {something like randomnum^N}. It's just another way of introducing random factors into the choice of winners and losers which should already have been accounted for in the heritability function.

The net result is a significant reduction in the effect of selection.

It would make more sense if it were described in terms of some other phenotype with an effect on fitness. The phenotype has a genetic component and an environmental (or random) component, i.e. has a heritability. The phenotype then confers a fitness, which is the probability of successful reproduction. The number of successful offspring is also drawn from a random distribution, which is what's being done in this bit of code (I guess treated as a binomial distribution).

Yes, I'm okay with that. That's how my own (rather primitive) model is structured. I'm not modeling recombination at this point, because I don't think that's where the problem lies. It's more basic than that. There's seems to be very little signal of selection. I'm still tinkering, but his results don't seem to jive.


You never step on the same tard twice—for it's not the same tard and you're not the same person.

  419 replies since Mar. 17 2009,11:00 < Next Oldest | Next Newest >  

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