Exploring Rich Biological Mechanisms in Evolutionary Computation and Genetics
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Presentation Transcript
FOGA “Round Table” Did we learn anything? UNAM, Mexico 11/01/07
Genetic diversity • Real biological systems change through much richer mechanisms than we use in EC • Can they be useful for us? • In what areas? Combinatorial optimization? • Should we try and model these? How? • Why are they there in biology? This could indicate where to use them in EC. • Are they of interest in Genetics? How do they think they may be modeled?
Modularity • There is complex cooperativity at all scales in living systems • This is not apparently present (not possibly present?) in EC or in Genetics. • Is it of any use in EC? Where? Combinatorial optimization? • How does one model so that it emerges without putting it in by hand? (epistasis induces correlation “by hand”).
Representations • Why are representations (geno-pheno map) so exceedingly complex in biology? • Even the most GA-like systems in biology (RNA world) have complicated maps • Do we need them? (Neutrality etc.) • If so, in what areas? Combinatorial optimization? • How does Genetics deal with it?
Mathematical modeling • Mathematical Modeling in EC and Genetics seems to be very similar (obviously?) • How to promote more transfer of knowledge? • Both “combinatorial optimization” – “GA” with a fixed fitness function(al) • How to do “real” calculations (numbers)? (Finite populations) • Why are the analogs of “practitioners” in genetics happier with theory than their EC colleagues? • Fitness – what is it good for? • Is it a barrier to “real evolution” as opposed to “breeding”
Where to go? • Just forget about its biological origins? • E.g. Evolutionary strategies for combinatorial optimization? • Take them more seriously and take a more modern point of view? • What “problems/areas” need more “biology”? • Both? How much of each? • Supply/demand