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



Posts: 2723
Joined: Sep. 2006

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

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

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.

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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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