title: Self-adaptation in evolving systems.
abstract: A theoretical and experimental analysis is made of the effects of self-adaptation in a simple evolving system. Specifically, we consider the effects of coding the mutation and crossover probabilities of a genetic algorithm evolving in certain model fitness landscapes. The resultant genotype-phenotype mapping is degenerate in fitness space, there being no direct selective advantage for one probability versus another. Thus there is a "symmetry" between various genotypes that all correspond to the same phenotype. We show that the action of mutation and crossover lifts this degeneracy, that is, the genetic operators induce a breaking of the genotype-phenotype symmetry, thus leading to a preference for those genotypes that propagate most successfully into future generations. We demonstrate that this induced symmetry breaking allows the system to self-adapt in a time-dependent environment.
authors.affiliation: Instituto de Ciencias Nucleares, UNAM, Circuito Exterior, A. Postal 70-543, México DF 04510. stephens@nuclecu.unam.mx
authors.forename: C R
authors.initials: CR
authors.lastname: Stephens
authors.forename: I
authors.initials: I
authors.lastname: García Olmedo
authors.forename: J
authors.initials: J
authors.lastname: Mora Vargas
authors.forename: H
authors.initials: H
authors.lastname: Waelbroeck
mesh_terms: D000222:Adaptation, Physiological; D000465:Algorithms; D001185:Artificial Intelligence; D005075:Biological Evolution; D008957:Models, Genetic; D010641:Phenotype