Discovery by Genetic Programming of a Cellular Automata Rule that is Better than any Known Rule for the Majority Classification Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{andre:1996:camc,
  author =       "David Andre and Forrest H {Bennett III} and 
                 John R. Koza",
  title =        "Discovery by Genetic Programming of a Cellular
                 Automata Rule that is Better than any Known Rule for
                 the Majority Classification Problem",
  booktitle =    "Genetic Programming 1996: Proceedings of the First
                 Annual Conference",
  editor =       "John R. Koza and David E. Goldberg and 
                 David B. Fogel and Rick L. Riolo",
  year =         "1996",
  month =        "28--31 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  pages =        "3--11",
  address =      "Stanford University, CA, USA",
  publisher =    "MIT Press",
  URL =          "http://www.genetic-programming.com/jkpdf/gp1996gkl.pdf",
  size =         "9 pages",
  abstract =     "It is difficult to program cellular automata. This is
                 especially true when the desired computation requires
                 global communication and global integration of
                 information across great distances in the cellular
                 space. Various human- written algorithms have appeared
                 in the past two decades for the vexatious majority
                 classification task for one-dimensional two-state
                 cellular automata. This paper describes how genetic
                 programming with automatically defined functions
                 evolved a rule for this task with an accuracy of
                 82.326%. This level of accuracy exceeds that of the
                 original 1978 Gacs-Kurdyumov-Levin (GKL) rule, all
                 other known human-written rules, and all other known
                 rules produced by automated methods. The rule evolved
                 by genetic programming is qualitatively different from
                 all previous rules in that it employs a larger and more
                 intricate repertoire of domains and particles to
                 represent and communicate information across the
                 cellular space.",
  URL =          "http://cognet.mit.edu/library/books/view?isbn=0262611279",
  notes =        "GP-96",
}

Genetic Programming entries for David Andre Forrest Bennett John Koza