Using Genetic Programming to Evolve Board Evaluation Functions for a Boardgame

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

@InProceedings{ferrer:1995:bef,
  author =       "Gabriel J. Ferrer and Worthy N. Martin",
  title =        "Using Genetic Programming to Evolve Board Evaluation
                 Functions for a Boardgame",
  booktitle =    "1995 IEEE Conference on Evolutionary Computation",
  year =         "1995",
  volume =       "2",
  pages =        "747",
  address =      "Perth, Australia",
  publisher_address = "Piscataway, NJ, USA",
  month =        "29 " # nov # " - 1 " # dec,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, Senet",
  broken =       "http://www.cs.virginia.edu/~gjf2a/work/papers/senet.ps",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/senet.ps.gz",
  size =         "6 pages",
  abstract =     "In this paper, we employ the genetic programming
                 paradigm to enable a computer to learn to play
                 strategies for the ancient Egyptian boardgame Senet by
                 evolving board evaluation functions. Formulating the
                 problem in terms of board evaluation functions made it
                 feasible to evaluate the fitness of game playing
                 strategies by using tournament-style fitness
                 evaluation. The game has elements of both strategy and
                 chance. Our approach learns strategies which enable the
                 computer to play consistently at a reasonably skillful
                 level.",
  notes =        "ICEC-95 http://www.io.org/~causal/c_p/cpec95.htm
                 Editors not given by IEEE, Organisers David Fogel and
                 Chris deSilva.

                 conference details at
                 http://ciips.ee.uwa.edu.au/~dorota/icnn95.html

                 Fitness given by knockout tournament, rank-proprtionate
                 selection, mutation and crossover, generational,
                 non-standard random initial population
                 creation/mutation/crossover, no size limit on programs.
                 2 non-seeded runs, 2 seeded runs (504 random + 8
                 different hand-coded). No discussion of statistical
                 significance of results.

                 ",
}

Genetic Programming entries for Gabriel J Ferrer Worthy N Martin

Citations