Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes

Abstract

In common genetic programming approaches, the space of genotypes, that is the search space, is identical to the space of phenotypes, that is the solution space. Facts and theories from molecular biology suggest the introduction of non-identical genospaces and phenospaces, and a generic genotype-phenotype mapping which maps unconstrained genotypes into syntactically correct phenotypes. Neutral variants come into effect due to this mapping. They enhance genetic diversity and allow for escaping local optima in phenospace via high-dimensional saddle surfaces in genospace. We propose a concrete mapping that maps linear binary genotypes into linear phenotypes of an arbitrary context-free programming language. Empirical results are presented which show that the mapping improves the performance of GP under mutation and reproduction. 1 Introduction Common GP approaches (e.g. "Koza (1992)") do not distinguish between a genotype, i.e. a point in search space, and its phen...