in reply to Re: JAPH-ing Genetically
in thread JAPH-ing Genetically

andye is right. Fitness function f must be continuus, so that for two similar individuals x1 and x2, f(x1) is similar to f(x2).

So, small causes (small random mutations) imply small changes (small variations of fitness).

If you want to apply the ideas of GA to evolve programs, you should explore the so-called field of Genetic Programming; a classic reference are Holland's books

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Re: Re: Re: JAPH-ing Genetically
by Anonymous Monk on May 23, 2001 at 17:33 UTC
    You could fuzz hard edges (go - no go) by statistical evaluation (Markov-Chains) with the statistical properties of Perl. Meaning if the program has the same statistical properties as Perl it is slightly fitter than when not, despite it not being valid Perl or if it is valid (which gives a large boost in FITNESS) but doesn't have the statistical properties of Perl it is slightly unfitter.