Competition, Coevolution and the Game of Tag

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

@InProceedings{Reynolds:1994:tag,
  author =       "Craig W. Reynolds",
  title =        "Competition, Coevolution and the Game of Tag",
  booktitle =    "Proceedings of the Fourth International Workshop on
                 the Synthesis and Simulation of Living Systems",
  year =         "1994",
  editor =       "Rodney A. Brooks and Pattie Maes",
  pages =        "59--69",
  address =      "MIT, Cambridge, MA, USA",
  month =        "6-8 " # jul,
  publisher =    "MIT Press",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/ftp.io.com/papers/cwrALifeIV.ps.Z",
  size =         "11 pages",
  abstract =     "Tag is a children's game based on symmetrical pursuit
                 and evasion. In these experiments, control programs for
                 mobile agents (simulated vehicles) are created through
                 artificial evolution, based on their skill at the game
                 of tag. Each controller is composed of distinct
                 behavior components for pursuit and evasion. A player's
                 fitness is based entirely on how well it performs in
                 competition with several other players chosen randomly
                 from the coevolving population of players. This
                 approach avoids the need for an expert player as a
                 fitness reference. In the beginning, the quality of
                 play is very low. This provides a fertile field for
                 slightly better strategies to exploit the weaknesses of
                 others. Through evolution, guided by competitive
                 fitness, increasingly better strategies emerge over
                 time.",
  notes =        "alife-4 Gives introduction to existing work on using
                 co-evolution in GPs and GAs. Uses Steady state GP with
                 tournament (7) selection. However 50% of deletions are
                 at random and 50% by inverse tournament. Some runs use
                 mutation. Some times uses Kinnear's Hoist crossover.

                 ",
}

Genetic Programming entries for Craig W Reynolds

Citations