Neutrality and variability: two sides of evolvability in linear genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Ting Hu and Wolfgang Banzhaf",
  title =        "Neutrality and variability: two sides of evolvability
                 in linear genetic programming",
  booktitle =    "GECCO '09: Proceedings of the 11th Annual conference
                 on Genetic and evolutionary computation",
  year =         "2009",
  editor =       "Guenther Raidl and Franz Rothlauf and 
                 Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and 
                 Mauro Birattari and Clare Bates Congdon and 
                 Martin Middendorf and Christian Blum and Carlos Cotta and 
                 Peter Bosman and Joern Grahl and Joshua Knowles and 
                 David Corne and Hans-Georg Beyer and Ken Stanley and 
                 Julian F. Miller and Jano {van Hemert} and 
                 Tom Lenaerts and Marc Ebner and Jaume Bacardit and 
                 Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and 
                 Thomas Jansen and Riccardo Poli and Enrique Alba",
  pages =        "963--970",
  address =      "Montreal",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "8-12 " # jul,
  organisation = "SigEvo",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-60558-325-9",
  bibsource =    "DBLP,",
  DOI =          "doi:10.1145/1569901.1570033",
  abstract =     "The notion of evolvability has been put forward to
                 describe the {"}core mechanism{"} of natural and
                 artificial evolution. Recently, studies have revealed
                 the influence of the environment upon a system's
                 evolvability. In this contribution, we study the
                 evolvability of a system in various environmental
                 situations. We consider neutrality and variability as
                 two sides of evolvability. The former makes a system
                 tolerant to mutations and provides a hidden staging
                 ground for future phenotypic changes. The latter
                 produces explorative variations yielding phenotypic
                 improvements. Which of the two dominates is influenced
                 by the environment. We adopt two tools for this study
                 of evolvability: 1) the rate of adaptive evolution,
                 which captures the observable adaptive variations
                 driven by evolvability; and 2) the variability of
                 individuals, which measures the potential of an
                 individual to vary functionally. We apply these tools
                 to a Linear Genetic Programming system and observe that
                 evolvability is able to exploit its two sides in
                 different environmental situations.",
  notes =        "GECCO-2009 A joint meeting of the eighteenth
                 international conference on genetic algorithms
                 (ICGA-2009) and the fourteenth annual genetic
                 programming conference (GP-2009).

                 ACM Order Number 910092.",

Genetic Programming entries for Ting Hu Wolfgang Banzhaf