Neutrality and the Evolvability of Boolean Function Landscape

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{yu:2001:EuroGP_neutrality,
  author =       "Tina Yu and Julian Miller",
  title =        "Neutrality and the Evolvability of {Boolean} Function
                 Landscape",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2001",
  year =         "2001",
  editor =       "Julian F. Miller and Marco Tomassini and 
                 Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and 
                 William B. Langdon",
  volume =       "2038",
  series =       "LNCS",
  pages =        "204--217",
  address =      "Lake Como, Italy",
  publisher_address = "Berlin",
  month =        "18-20 " # apr,
  organisation = "EvoNET",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, Neutrality,
                 Evolvability, Boolean function landscape, Neutral
                 mutation, Exploration vs. Exploitation, Graph-based
                 Genetic Programming",
  ISBN =         "3-540-41899-7",
  URL =          "http://www.cs.mun.ca/~tinayu/index_files/addr/public_html/neutrality.pdf",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=204",
  size =         "14 pages",
  abstract =     "This work is a study of neutrality in the context of
                 Evolutionary Computation systems. In particular, we
                 introduce the use of explicit neutrality with an
                 integer string coding scheme to allow neutrality to be
                 measured during evolution. We tested this method on a
                 Boolean benchmark problem. The experimental results
                 indicate that there is a positive relationship between
                 neutrality and evolvability: neutrality improves
                 evolvability. We also identify four characteristics of
                 adaptive/neutral mutations that are associated with
                 high evolvability. They may be the ingredients in
                 designing effective Evolutionary Computation systems
                 for the Boolean class problem.",
  notes =        "EuroGP'2001, part of \cite{miller:2001:gp}",
}

Genetic Programming entries for Tina Yu Julian F Miller

Citations