Genetic Programming of an Artificial Neural Network for Robust Control of a 2-D Path Following Robot

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@InProceedings{Roy:2008:IDETC/CIE,
  author =       "Anthony M. Roy and Erik K. Antonsson and 
                 Andrew A. Shapiro",
  title =        "Genetic Programming of an Artificial Neural Network
                 for Robust Control of a 2-D Path Following Robot",
  booktitle =    "28th Computers and Information in Engineering
                 Conference IDETC/CIE2008",
  year =         "2008",
  volume =       "1",
  pages =        "799--805",
  address =      "Brooklyn, New York, USA",
  month =        aug # " 3-6",
  publisher =    "ASME",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-0-7918-4325-3",
  DOI =          "doi:10.1115/DETC2008-50137",
  abstract =     "Genetic Programs that have phenotypes created by the
                 application of genotypes comprising rules are robust
                 and highly scalable. Such encodings are useful for
                 complex applications such as controller design. This
                 paper outlines an evolutionary algorithm capable of
                 creating a controller for 2 DOF, path following robot.
                 The controllers are embodied by Artificial Neural
                 Networks capable of full functionality despite multiple
                 failures.",
}

Genetic Programming entries for Anthony M Roy Erik K Antonsson Andrew A Shapiro

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