Population Exploration on Genotype Networks in Genetic Programming

  • Ting Hu
  • Wolfgang Banzhaf
  • Jason H. Moore
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8672)

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.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ting Hu
    • 1
  • Wolfgang Banzhaf
    • 2
  • Jason H. Moore
    • 1
  1. 1.Computational Genetics Laboratory, Geisel School of MedicineDartmouth CollegeLebanonUSA
  2. 2.Department of Computer ScienceMemorial UniversitySt. John’sCanada

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