Genetic Programming For Automatic Design Of Self-Adaptive Robots

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{calderoni:1998:GPadsar,
  author =       "Stephane Calderoni and Pierre Marcenac",
  title =        "Genetic Programming For Automatic Design Of
                 Self-Adaptive Robots",
  booktitle =    "Proceedings of the First European Workshop on Genetic
                 Programming",
  year =         "1998",
  editor =       "Wolfgang Banzhaf and Riccardo Poli and 
                 Marc Schoenauer and Terence C. Fogarty",
  volume =       "1391",
  series =       "LNCS",
  pages =        "163--177",
  address =      "Paris",
  publisher_address = "Berlin",
  month =        "14-15 " # apr,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-64360-5",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/13194/http:zSzzSzwww.univ-reunion.frzSz~caldezSzpublicationszSzpaperszSzlncs1391.pdf/calderoni98genetic.pdf",
  URL =          "http://citeseer.ist.psu.edu/267374.html",
  DOI =          "doi:10.1007/BFb0055936",
  size =         "15 pages",
  abstract =     "The general framework tackled in this paper is the
                 automatic generation of intelligent collective
                 behaviors using genetic programming and reinforcement
                 learning. We define a behavior-based system relying on
                 automatic design process using artificial evolution to
                 synthesize high level behaviors for autonomous agents.
                 Behavioral strategies are described by tree-based
                 structures, and manipulated by genetic evolving
                 processes. Each strategy is dynamically evaluated
                 during simulation, and weighted by an adaptative value.
                 This value is a quality factor that reflects the
                 relevance of a strategy as a good solution for the
                 learning task. It is computed using heterogeneous
                 reinforcement techniques associating immediate and
                 delayed reinforcements as dynamic progress estimators.
                 This work has been tested upon a canonical
                 experimentation framework: the foraging robots problem.
                 Simulations have been conducted and have produced some
                 promising results.",
  notes =        "EuroGP'98",
  affiliation =  "Iremia - Universite de La Reunion 15, Avenue Rene
                 Cassin BP 7151 97715 Saint-Denis messag cedex 9 15,
                 Avenue Rene Cassin BP 7151 97715 Saint-Denis messag
                 cedex 9",
}

Genetic Programming entries for Stephane Calderoni Pierre Marcenac

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