Evolving Vision Controllers with a Two-Phase Genetic Programming System Using Imitation

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Renaud Barate and Antoine Manzanera",
  title =        "Evolving Vision Controllers with a Two-Phase Genetic
                 Programming System Using Imitation",
  booktitle =    "From Animals to Animats 10, Proceedings of the 10th
                 International Conference on Simulation of Adaptive
                 Behavior, SAB 2008",
  year =         "2008",
  editor =       "Minoru Asada and John C. T. Hallam and 
                 Jean-Arcady Meyer and Jun Tani",
  series =       "Lecture Notes in Computer Science",
  volume =       "5040",
  pages =        "73--82",
  address =      "Osaka, Japan",
  month =        jul # " 7-12",
  publisher =    "Springer",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-540-69133-4",
  DOI =          "doi:10.1007/978-3-540-69134-1_8",
  abstract =     "We present a system that automatically selects and
                 parameterises a vision based obstacle avoidance method
                 adapted to a given visual context. This system uses
                 genetic programming and a robotic simulation to
                 evaluate the candidate algorithms. As the number of
                 evaluations is restricted, we introduce a novel method
                 using imitation to guide the evolution toward promising
                 solutions. We show that for this problem, our two-phase
                 evolution process performs better than other
  notes =        "part of \cite{DBLP:conf/sab/2008}",
  notes =        "From Animals to Animats 10",

Genetic Programming entries for Renaud Barate Antoine Manzanera