Iterated Mutual Observation with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Peter Dittrich and Thomas Kron and Christian Kuck and 
                 Wolfgang Banzhaf",
  title =        "Iterated Mutual Observation with Genetic Programming",
  journal =      "Sozionik Aktuell",
  year =         "2001",
  volume =       "2",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming",
  citeseer-isreferencedby = "oai:CiteSeerPSU:91154;
  citeseer-references = "oai:CiteSeerPSU:468369; oai:CiteSeerPSU:354356;
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:444392",
  rights =       "unrestricted",
  URL =          "",
  URL =          "",
  abstract =     "This paper introduces a simple model of interacting
                 agents that learn to predict each other. For learning
                 to predict the other's intended action we apply genetic
                 programming. The strategy of an agent is rational and
                 fixed. It does not change like in classical iterated
                 prisoners dilemma models. Furthermore the number of
                 actions an agent can choose from is infinite.
                 Preliminary simulation results are presented. They show
                 that by varying the population size of genetic
                 programming, different learning characteristics can
                 easily be achieved, which lead to quite different
                 communication patterns.",
  notes =        "",

Genetic Programming entries for Peter Dittrich Thomas Kron Christian Kuck Wolfgang Banzhaf