Genetic Programming Using Mutation, Reproduction and Genotype-phenotype Mapping from Linear Binary Genomes into Linear Lalr(1) Phenotypes Paper Category: Genetic Programming (gp)

In common GP approaches, the space of genotypes (search space) is identical to the space of phenotypes (solution space). Facts and theories from molecular biology suggest the introduction of non-identical genospaces and phenospaces, and a generic genotype-phenotype mapping (GPM) which maps unconstrained genotypes into syntactically correct phenotypes. Neutral variants come into eeect due to GPM. They enhance genetic diversity and allow for escaping local optima in phenospace via high-dimensional saddle surfaces in genospace. We propose a concrete GPM which maps linear binary genotypes into linear phenotypes of an arbitrary LALR(1) programming language. Empirical results are presented which show that the GPM improves the performance of GP under mutation and reproduction. 1 Introduction Common GP approaches (e.g. 1]) do not distinguish between a genotype, i.e. a point in search space, and its phenotype, i.e. a point in solution space, that is search space and solution space are identical.