The Evolution of Genetic Code in Genetic Programming

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

@InProceedings{keller:1999:TEGCGP,
  author =       "Robert E. Keller and Wolfgang Banzhaf",
  title =        "The Evolution of Genetic Code in Genetic Programming",
  booktitle =    "Proceedings of the Genetic and Evolutionary
                 Computation Conference",
  year =         "1999",
  editor =       "Wolfgang Banzhaf and Jason Daida and 
                 Agoston E. Eiben and Max H. Garzon and Vasant Honavar and 
                 Mark Jakiela and Robert E. Smith",
  volume =       "2",
  pages =        "1077--1082",
  address =      "Orlando, Florida, USA",
  publisher_address = "San Francisco, CA 94104, USA",
  month =        "13-17 " # jul,
  publisher =    "Morgan Kaufmann",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-55860-611-4",
  URL =          "http://web.cs.mun.ca/~banzhaf/papers/t.ps.gz",
  URL =          "http://citeseer.ist.psu.edu/244531.html",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-438.pdf",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-438.ps",
  abstract =     "In most Genetic Programming (GP) approaches, the space
                 of genotypes, that is the search space, is identical to
                 the space of phenotypes, that is the solution space.
                 Developmental approaches, like Developmental Genetic
                 Programming (DGP), distinguish between genotypes and
                 phenotypes and use a genotypephenotype mapping prior to
                 fitness evaluation of a phenotype. To perform this
                 mapping, DGP uses a problem-specific manually designed
                 genetic code, that is a mapping from genotype
                 components to phenotype components. The employed
                 genetic code is critical for the performance of the
                 underlying search process. Here, the evolution of
                 genetic code is introduced as a novel approach for
                 enhancing the search process. It is hypothesized that
                 code evolution improves the performance of
                 developmental approaches by enabling them to
                 beneficially adapt the fitness landscape during search.
                 As the first step of investigation, this article
                 empirically shows the operativeness of code evol...",
  notes =        "GECCO-99 A joint meeting of the eighth international
                 conference on genetic algorithms (ICGA-99) and the
                 fourth annual genetic programming conference (GP-99)",
}

Genetic Programming entries for Robert E Keller Wolfgang Banzhaf

Citations