Genetic Programming Controlling a Miniature Robot

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

@InProceedings{nordin:1995:robot,
  author =       "Peter Nordin and Wolfgang Banzhaf",
  title =        "Genetic Programming Controlling a Miniature Robot",
  booktitle =    "Working Notes for the AAAI Symposium on Genetic
                 Programming",
  year =         "1995",
  editor =       "E. V. Siegel and J. R. Koza",
  pages =        "61--67",
  address =      "MIT, Cambridge, MA, USA",
  publisher_address = "445 Burgess Drive, Menlo Park, CA 94025, USA",
  month =        "10--12 " # nov,
  publisher =    "AAAI",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.aaai.org/Papers/Symposia/Fall/1995/FS-95-01/FS95-01-008.pdf",
  URL =          "http://coblitz.codeen.org:3125/citeseer.ist.psu.edu/cache/papers/cs/599/ftp:zSzzSzlumpi.informatik.uni-dortmund.dezSzpubzSzbiocompzSzpaperszSzAAAI-robot.pdf/nordin95genetic.pdf",
  URL =          "http://citeseer.ist.psu.edu/nordin95genetic.html",
  URL =          "http://www.aaai.org/Library/Symposia/Fall/fs95-01.php",
  size =         "6.05 pages",
  abstract =     "We have evaluated the use of Genetic Programming to
                 directly control a miniature robot. The goal of the
                 GP-system was to evolve real-time obstacle avoiding
                 behaviour from sensorial data. The evolved programs are
                 used in a sense-think-act context. We employed a novel
                 technique to enable real time learning with a real
                 robot. The technique uses a probabilistic sampling of
                 the environment where each individual is tested on a
                 new real-time fitness case in a tournament selection
                 procedure. The fitness has a pain and a pleasure part.
                 The negative part of fitness, the pain, is simply the
                 sum of the proximity sensor values. In order to keep
                 the robot from standing still or gyrating, it has a
                 pleasure component of fitness. It gets pleasure from
                 going straight and fast. The evolved algorithm shows
                 robust performance even if the robot is lifted and
                 placed in a completely different environment or if
                 obstacles are moved around.",
  notes =        "Khepera Sun workstation. Steady state tournament
                 selection, Pop=30. Each fitness case lasts 400
                 milliseconds (run 40-60 minutes) CGPS Sun-4 machine
                 code linear GP

                 AAAI-95f GP. Part of \cite{siegel:1995:aaai-fgp} {\em
                 Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em
                 email} info@aaai.org {\em URL:}
                 http://www.aaai.org/

                 See also \cite{nordin:1996:aigp2}",
}

Genetic Programming entries for Peter Nordin Wolfgang Banzhaf

Citations