Emergent Cooperation for Multiple Agents Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{iba:1996:ecmaPPSN,
  author =       "Hitoshi Iba",
  title =        "Emergent Cooperation for Multiple Agents Using Genetic
                 Programming",
  booktitle =    "Parallel Problem Solving from Nature IV, Proceedings
                 of the International Conference on Evolutionary
                 Computation",
  year =         "1996",
  editor =       "Hans-Michael Voigt and Werner Ebeling and 
                 Ingo Rechenberg and Hans-Paul Schwefel",
  series =       "LNCS",
  volume =       "1141",
  pages =        "32--41",
  address =      "Berlin, Germany",
  publisher_address = "Heidelberg, Germany",
  month =        "22-26 " # sep,
  publisher =    "Springer Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-61723-X",
  DOI =          "doi:10.1007/3-540-61723-X_967",
  size =         "10 pages",
  abstract =     "This paper presents the emergence of the cooperative
                 behaviour for the multiple agents by means of Genetic
                 Programming (GP). Our experimental domain is the Tile
                 World, a multi-agent test bed [Pollack90]. The world
                 consists of a simulated robot agent and a simulated
                 environment which is both dynamic and unpredictable.
                 For the purpose of evolving the cooperative behavior,
                 we propose three types of strategies, i.e, homogeneous
                 breeding, heterogeneous breeding, and co-evolutionary
                 breeding. The effectiveness of these three types of
                 GP-based multi-agent learning is discussed with
                 comparative experiments.",
  notes =        "http://lautaro.fb10.tu-berlin.de/ppsniv.html PPSN4
                 Comparison of homogeneous, heterogeneous and
                 co-evolutionary breeding on 'Tile world' simulated
                 environment problem.",
  affiliation =  "Electrotechnical Laboratory (ETL) Machine Inference
                 Section 1-1-4 Umezono, Tsukuba Science City 305 Ibaraki
                 Japan 1-1-4 Umezono, Tsukuba Science City 305 Ibaraki
                 Japan",
}

Genetic Programming entries for Hitoshi Iba

Citations