Grammar-Guided Genetic Programming and Automatically Defined Functions

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

@InProceedings{sbia2002meta031,
  author =       "Ernesto Rodrigues and Aurora Pozo",
  title =        "Grammar-Guided Genetic Programming and Automatically
                 Defined Functions",
  booktitle =    "Advances in Artificial Intelligence: 16th Brazilian
                 Symposium on Artificial Intelligence, SBIA 2002,
                 Proceedings",
  year =         "2002",
  editor =       "Guilherme Bittencourt and Geber Ramalho",
  volume =       "2507",
  series =       "LNAI",
  pages =        "324--333",
  address =      "Porto de Galinhas/Recife, Brazil",
  month =        "11-14 " # nov,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, ADFs",
  ISBN =         "3-540-00124-7",
  ISSN =         "0302-9743",
  DOI =          "doi:10.1007/3-540-36127-8_31",
  abstract =     "Genetic Programming (GP) is a powerful software
                 induction technique that has been recently applied for
                 solving a wide variety of problems. Attempts to extend
                 GP have focussed on applying type restrictions to the
                 language to control genetic operators and to ensure
                 that only valid programs are created. In this sense,
                 the use of context free grammar (CFG) was proposed.
                 This work studies the use of a CFG to define the
                 structure of the initial population and direct
                 crossover and mutation operators. Chameleon, a
                 Grammar-Guided Genetic Programming system (GGGP) is
                 also presented. On a suite of experiments composed of
                 even-parity problems, the performance of Chameleon is
                 compared to traditional GP. Furthermore, the automatic
                 discovery of sub-functions, one of the most important
                 research areas in GP, is also explored. We describe how
                 to use ADFs with GGGP and, using Chameleon, we
                 demonstrate that GGGP has similar results to Koza's
                 Automatically Defined Functions (ADF) approach.",
  notes =        "SBIA 2002

                 Fundac\~{a}o de Estudos Sociais do Parana, Departamento
                 de Informatica, Rua General Carneiro, 216,Centro,
                 80060-150, Curitiba, Parana, Brazil",
}

Genetic Programming entries for Ernesto L M Rodrigues Aurora Trinidad Ramirez Pozo

Citations