Evolving Behavioral Strategies in Predators and Prey

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

  author =       "Thomas Haynes and Sandip Sen",
  title =        "Evolving Behavioral Strategies in Predators and Prey",
  booktitle =    "Adaptation and Learning in Multiagent Systems",
  publisher =    "Springer Verlag",
  year =         "1995",
  editor =       "Gerhard Wei{\ss} and Sandip Sen",
  volume =       "1042",
  series =       "Lecture Notes in Artificial Intelligence",
  pages =        "113--126",
  address =      "Berlin, Germany",
  keywords =     "genetic algorithms, genetic programming, STGP",
  isbn13 =       "978-3-540-60923-0",
  DOI =          "doi:10.1007/3-540-60923-7_22",
  abstract =     "The predator/prey domain is used to conduct research
                 in Distributed Artificial Intelligence. Genetic
                 Programming is used to evolve behavioural strategies
                 for the predator agents. To further the utility of the
                 predator strategies, the prey population is allowed to
                 evolve at the same time. The expected competitive
                 learning cycle did not surface. This failing is
                 investigated, and a simple prey algorithm surfaces,
                 which is consistently able to evade capture from the
                 predator algorithms.",
  size =         "14 pages",
  notes =        "Published in 1996?

  affiliation =  "The University of Tulsa Department of Mathematical &
                 Computer Sciences USA USA",

Genetic Programming entries for Thomas D Haynes Sandip Sen