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