mGGA: The meta-Grammar Genetic Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{eurogp:ONeillB05,
  author =       "Michael O'Neill and Anthony Brabazon",
  editor =       "Maarten Keijzer and Andrea Tettamanzi and 
                 Pierre Collet and Jano I. {van Hemert} and Marco Tomassini",
  title =        "m{GGA}: The meta-Grammar Genetic Algorithm",
  booktitle =    "Proceedings of the 8th European Conference on Genetic
                 Programming",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3447",
  year =         "2005",
  address =      "Lausanne, Switzerland",
  month =        "30 " # mar # " - 1 " # apr,
  organisation = "EvoNet",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-25436-6",
  pages =        "311--320",
  URL =          "http://springerlink.metapress.com/openurl.asp?genre=article&issn=0302-9743&volume=3447&spage=311",
  doi =          "doi:10.1007/b107383",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  abstract =     "A novel Grammatical Genetic Algorithm, the
                 meta-Grammar Genetic Algorithm (mGGA) is presented. The
                 mGGA borrows a grammatical representation and the ideas
                 of modularity and reuse from Genetic Programming, and
                 in particular an evolvable grammar representation from
                 Grammatical Evolution by Grammatical Evolution. We
                 demonstrate its application to a number of benchmark
                 problems where significant performance gains are
                 achieved when compared to static grammars.",
  notes =        "Part of \cite{keijzer:2005:GP} EuroGP'2005 held in
                 conjunction with EvoCOP2005 and EvoWorkshops2005",
}

Genetic Programming entries for Michael O'Neill Anthony Brabazon