Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Back:2004:UPP,
  author =       "Thomas Baeck and Ron Breukelaar and Lars Willmes",
  title =        "Inverse Design of Cellular Automata by Genetic
                 Algorithms: An Unconventional Programming Paradigm",
  booktitle =    "Unconventional Programming Paradigms: International
                 Workshop UPP 2004",
  year =         "2004",
  editor =       "Jean-Pierre Banatre and Pascal Fradet and 
                 Jean-Louis Giavitto and Olivier Michel",
  volume =       "3566",
  series =       "LNCS",
  pages =        "161--172",
  address =      "Le Mont Saint Michel, France",
  month =        sep # " 15-17",
  publisher =    "Springer",
  note =         "Revised Selected and Invited Papers, 2005",
  keywords =     "genetic algorithms, genetic programming, CA",
  isbn13 =       "978-3-540-31482-0",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.535.7340",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.535.7340",
  broken =       "http://www.liacs.nl/~rbreukel/publications/UPP.pdf",
  URL =          "https://doi.org/10.1007/11527800_13",
  DOI =          "doi:10.1007/11527800_13",
  size =         "12 pages",
  abstract =     "Evolving solutions rather than computing them
                 certainly represents an unconventional programming
                 approach. The general methodology of evolutionary
                 computation has already been known in computer science
                 since more than 40 years, but their use to program
                 other algorithms is a more recent invention. In this
                 paper, we outline the approach by giving an example
                 where evolutionary algorithms serve to program cellular
                 automata by designing rules for their iteration. Three
                 different goals of the cellular automata designed by
                 the evolutionary algorithm are outlined, and the
                 evolutionary algorithm indeed discovers rules for the
                 CA which solve these problems efficiently.",
}

Genetic Programming entries for Thomas Back Ron Breukelaar Lars Willmes

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