Neutrality, Robustness, and Evolvability in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Ting Hu and Wolfgang Banzhaf",
  title =        "Neutrality, Robustness, and Evolvability in Genetic
  booktitle =    "Genetic Programming Theory and Practice XIV",
  year =         "2016",
  editor =       "Rick Riolo and Bill Worzel and Brian Goldman and 
                 Bill Tozier",
  address =      "Ann Arbor, USA",
  month =        "19-21 " # may,
  publisher =    "Springer",
  note =         "Forthcoming",
  keywords =     "genetic algorithms, genetic programming, Linear
                 Genetic Programming, Robustness, Evolvability,
                 Neutrality, Redundancy, Genotype-to-phenotype mapping,
                 Genotype network, Phenotype network",
  isbn13 =       "978-3-319-97087-5",
  URL =          "",
  URL =          "",
  size =         "16 pages",
  abstract =     "Redundant mapping from genotype to phenotype is common
                 in evolutionary algorithms, especially in genetic
                 programming (GP). Such a redundancy can lead to
                 neutrality, where mutations to a genotype may not alter
                 its phenotypic outcome. The effects of neutrality can
                 be better understood by quantitatively analysing its
                 two observed properties, i.e., robustness and
                 evolvability. In this study, we examine a compact
                 Linear GP algorithm, characterize its entire genotype,
                 phenotype, and fitness networks, and quantitatively
                 measure robustness and evolvability at the genotypic,
                 phenotypic, and fitness levels. We investigate the
                 relationship of robustness and evolvability at those
                 different levels. We use an ensemble of random walks
                 and hill climbs to study how robustness and
                 evolvability and the structure of genotypic,
                 phenotypic, and fitness networks influence the
                 evolutionary search process.",
  notes =        "

                 Part of \cite{Tozier:2016:GPTP} to be published after
                 the workshop",

Genetic Programming entries for Ting Hu Wolfgang Banzhaf