Evolving Behavioral Strategies in Predators and Prey

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

  author =       "Thomas Haynes and Sandip Sen",
  title =        "Evolving Behavioral Strategies in Predators and Prey",
  pages =        "113--126",
  editor =       "Gerhard Wei{\ss} and Sandip Sen",
  booktitle =    "Adaptation and Learning in Multi--Agent Systems",
  year =         "1996",
  publisher =    "Springer Verlag",
  series =       "Lecture Notes in Artificial Intelligence",
  address =      "Berlin, Germany",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "see also \cite{Hayes:1995:ebspp}",
  broken =       "http://euler.mcs.utulsa.edu/~haynes/icjai95.ps",
  URL =          "http://citeseer.ist.psu.edu/rd/13718071%2C21714%2C1%2C0.25%2CDownload/http://coblitz.codeen.org:3125/citeseer.ist.psu.edu/cache/papers/cs/734/http:zSzzSzwww.cs.twsu.eduzSz%7EhayneszSzicjai95.pdf/haynes96evolving.pdf",
  URL =          "http://citeseer.ist.psu.edu/haynes96evolving.html",
  abstract =     "The predator/prey domain is used to conduct research
                 in Distributed Artificial Intelligence. Genetic
                 Programing is used to evolve behavioral 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.",

Genetic Programming entries for Thomas D Haynes Sandip Sen