Discovery of the Boolean Functions to the Best Density-Classification Rules Using Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  title =        "Discovery of the {Boolean} Functions to the Best
                 Density-Classification Rules Using Gene Expression
  author =       "C\^andida Ferreira",
  editor =       "James A. Foster and Evelyne Lutton and 
                 Julian Miller and Conor Ryan and Andrea G. B. Tettamanzi",
  booktitle =    "Genetic Programming, Proceedings of the 5th European
                 Conference, EuroGP 2002",
  volume =       "2278",
  series =       "LNCS",
  pages =        "50--59",
  publisher =    "Springer-Verlag",
  address =      "Kinsale, Ireland",
  publisher_address = "Berlin",
  month =        "3-5 " # apr,
  year =         "2002",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-43378-3",
  DOI =          "doi:10.1007/3-540-45984-7_5",
  abstract =     "Cellular automata are idealized versions of massively
                 parallel, decentralized computing systems capable of
                 emergent behaviours. These complex behaviors result
                 from the simultaneous execution of simple rules at
                 multiple local sites. A widely studied behavior
                 consists of correctly determining the density of an
                 initial configuration, and both human and
                 computer-written rules have been found that perform
                 with high efficiency at this task. However, the two
                 best rules for the density-classification task,
                 Coevolution1 and Coevolution2, were discovered using a
                 coevolutionary algorithm in which a genetic algorithm
                 evolved the rules and, therefore, only the output bits
                 of the rules are known. However, to understand why
                 these and other rules perform so well and how the
                 information is transmitted throughout the cellular
                 automata, the Boolean expressions that orchestrate this
                 behaviour must be known. The results presented in this
                 work are a contribution in that direction.",
  notes =        "EuroGP'2002, part of \cite{lutton:2002:GP}",

Genetic Programming entries for Candida Ferreira