[Icfp04-discuss] Evolutionary Ants

[Carlos Scheidegger]

I think there's probably some good compromise between the compiler
approach and the evolutionary approach: I can envision more
interesting mutation operators applied to high-level code. This has
the added approach of low-level ant code being independent of the
high-level code in which the mutations are being operated. I think I
recall reading about some advantages of having distinct 'genotypes'
and 'fenotypes'. Also, genetic programming deals explicitly with
evolving programs, so you could probably borrow a lot of techniques.

-carlos

On Fri, 11 Jun 2004 10:25:26 +0200, detlef at dpleiss.de <detlef at dpleiss.de> wrote:
> 
> On 9 Jun 2004 at 11:52, Jens Hauke wrote:
> 
> > Maybe try the same with less than 300 lines? I got much better results
> > with very short ant programs (the search space is much smaller and
> > good strategys dont need much code). The next improvement (i think):
> > leave the goto's in each line nearly untouched to safe the program
> > flow.
> 
> I guess 10000 random lines contain a lot of "dead strands", code that is never reached.
> I assume if running different 10000 lines random code programs through the optimizers
> as discussed lately you'll effectively get random size programs.
> 
> I used to change just one line of code per generation. If such a change happens in dead
> code it effectively changes nothing. Then again in the other case it might activate a until-
> then dead strand, so one line could make a big difference.
> 
> Anyway, I'm going to try what happens if I change more than one line of code per
> generation.
> 
> 
> 
> ciao - Det.
> 
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