 |
    |
Population Exploration on Genotype Networks in Genetic Programming
Ting Hu1, Wolfgang Banzhaf2, and Jason H. Moore1
1Computational Genetics Laboratory, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
ting.hu@dartmouth.edu
jason.h.moore@dartmouth.edu
2Department of Computer Science, Memorial University, St. John’s, NL, A1B 3X5, Canada
banzhaf@mun.ca
Abstract. Redundant genotype-to-phenotype mappings are pervasive in evolutionary computation. Such redundancy allows populations to expand in neutral genotypic regions where mutations to a genotype do not alter the phenotypic outcome. Genotype networks have been proposed as a useful framework to characterize the distribution of neutrality among genotypes and phenotypes. In this study, we examine a simple Genetic Programming model that has a finite and compact genotype space by characterizing its genotype networks. We study the topology of individual genotype networks underlying unique phenotypes, investigate the genotypic properties as vertices in genotype networks, and discuss the correlation of these network properties with robustness and evolvability. Using GP simulations of a population, we demonstrate how an evolutionary population diffuses on genotype networks.
LNCS 8672, p. 424 ff.
lncs@springer.com
© Springer International Publishing Switzerland 2014