Identifying Cellular Automata Rules

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@Article{DBLP:journals/jca/MaedaS07,
  author =       "Ken-ichi Maeda and Chiaki Sakama",
  title =        "Identifying Cellular Automata Rules",
  journal =      "Journal of Cellular Automata",
  year =         "2007",
  volume =       "2",
  number =       "1",
  pages =        "1--20",
  keywords =     "genetic algorithms, genetic programming, Cellular
                 automata, identification problem, decision tree",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  URL =          "http://www.oldcitypublishing.com/JCA/JCAabstracts/JCA2.1abstracts/JCAv2n1p1-20Maeda.html",
  URL =          "http://www.sys.wakayama-u.ac.jp/~sakama/papers/jca07.pdf",
  size =         "20 pages",
  abstract =     "This paper studies a method for identifying cellular
                 automata rules (CA rules). Given a sequence of CA
                 configurations, we first seek an appropriate
                 neighbourhood of a cell and collect cellular changes of
                 states as evidences. The collected evidences are then
                 classified using a decision tree, which is used for
                 constructing CA transition rules. Conditions for
                 classifying evidences in a decision tree are computed
                 using genetic programming. We perform experiments using
                 several types of CAs and verify that the proposed
                 method successfully identifies correct CA rules.",
}

Genetic Programming entries for Ken-ichi Maeda Chiaki Sakama

Citations