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Re: Selection Functions
From: |
Heinzelmann Matthias |
Subject: |
Re: Selection Functions |
Date: |
Fri, 5 May 2000 10:20:57 +0200 (CEST) |
Michael, why use individual modelling when what you really do is use an
algorythm that approaches the problem from the macro-level. Why not let
individuals meet and then let them decide to breed according to some
'attractiveness'. Seems to be more bottom-up.
On Fri, 5 May 2000, Michael Stillwell wrote:
> I'm working on a GA-like system in which the probability that a bug is
> chosen to breed is related to its fitness. It appears that the
> traditional way to do this is to use "roulette wheel selection"--each
> bug gets a slice of the wheel in proportion to its fitness, the wheel
> is spun, and the bug associated with the point where the wheel ended
> up is gets to breed.
>
> Do other "selection functions" exist? My problem with roulette wheel
> selection is that it offers no real control over the distribution of
> the expected number of offspring. For example, if all the bugs (or
> "solutions", etc.) are *equally* *fit*, then there is an e^-1 chance
> (approx 36%) that a bug will not be selected at all. This doesn't
> seem to mirror what happens in nature, where one might expect each bug
> to have one child (or close to it).
>
> (I am aware of one other "selection function"--Goldberg's "Genetic
> Algorithms in Search, Optimisation and Machine Learning" describes an
> "expected value model" that effectively reduces the size of the slice
> granted to a bug every time it is selected for reproduction, but I
> would be interested to hear of others.)
>
>
>
>
>
>
> Michael
>
>
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please send a message to <address@hidden> with "help" in the
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