Automatically Defined Functions in Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "C\^{a}ndida Ferreira",
  title =        "Automatically Defined Functions in Gene Expression
  year =         "2006",
  booktitle =    "Genetic Systems Programming: Theory and Experiences",
  pages =        "21--56",
  volume =       "13",
  series =       "Studies in Computational Intelligence",
  editor =       "Nadia Nedjah and Ajith Abraham and 
                 Luiza {de Macedo Mourelle}",
  publisher =    "Springer",
  address =      "Germany",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, ADF",
  ISBN =         "3-540-29849-5",
  URL =          "",
  DOI =          "doi:10.1007/3-540-32498-4_2",
  abstract =     "

                 In this chapter it is shown how Automatically Defined
                 Functions are encoded in the genotype/phenotype system
                 of Gene Expression Programming. As an introduction, the
                 fundamental differences between Gene Expression
                 Programming and its predecessors, Genetic Algorithms
                 and Genetic Programming, are briefly summarized so that
                 the evolutionary advantages of Gene Expression
                 Programming are better understood. The introduction
                 proceeds with a detailed description of the
                 architecture of the main players of Gene Expression
                 Programming (chromosomes and expression trees),
                 focusing mainly on the interactions between them and
                 how the simple, yet revolutionary, structure of the
                 chromosomes allows the efficient, unconstrained
                 exploration of the search space. The work proceeds with
                 an introduction to Automatically Defined Functions and
                 how they are implemented in Gene Expression
                 Programming. Furthermore, the importance of
                 Automatically Defined Functions in Evolutionary
                 Computation is thoroughly analyzed by comparing the
                 performance of sophisticated learning systems with
                 Automatically Defined Functions with much simpler ones
                 on the sextic polynomial problem.",
  notes =        ",11855,5-146-22-92733168-0,00.html",

Genetic Programming entries for Candida Ferreira