Meta-Evolution in Graph GP

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{kantschik:1999:m-egGP,
  author =       "Wolfgang Kantschik and Peter Dittrich and 
                 Markus Brameier and Wolfgang Banzhaf",
  title =        "Meta-Evolution in Graph GP",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'99",
  year =         "1999",
  editor =       "Riccardo Poli and Peter Nordin and 
                 William B. Langdon and Terence C. Fogarty",
  volume =       "1598",
  series =       "LNCS",
  pages =        "15--28",
  address =      "Goteborg, Sweden",
  publisher_address = "Berlin",
  month =        "26-27 " # may,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-65899-8",
  URL =          "http://ls11-www.informatik.uni-dortmund.de/people/wkantsch/Publications/metaEuroGP99.ps.gz",
  URL =          "http://citeseer.ist.psu.edu/475739.html",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=1598&spage=15",
  DOI =          "doi:10.1007/3-540-48885-5_2",
  abstract =     "In this contribution we introduce the evolution of
                 operators for Genetic Programming by means of Genetic
                 Programming. Specifically, meta-evolution of
                 recombination operators in graph-based GP is applied
                 and compared to other methods for the variation of
                 recombination operators in graph-based GP. We
                 demonstrate that a straightforward application of
                 recombination operators onto themselves does not work
                 well. After introducing an additional level of
                 recombination operators (the meta level) which are
                 recombining a pool of recombination operators, even
                 self-recombination on the additional becomes feasible.
                 We show that the overall performance of this system is
                 better than in other variants of graph GP. As a test
                 problem we use speaker recognition",
  notes =        "EuroGP'99, part of \cite{poli:1999:GP}

                 Genome is a graph. Evolves genetic operators (also
                 represented as graphs) which act on the graphs.",
}

Genetic Programming entries for Wolfgang Kantschik Peter Dittrich Markus Brameier Wolfgang Banzhaf

Citations