Building Agents with Memory: An Approach using Genetically Programmed Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Arlindo Silva and Ana Neves and Ernesto Costa",
  title =        "Building Agents with Memory: An Approach using
                 Genetically Programmed Networks",
  booktitle =    "Proceedings of the Congress on Evolutionary
  year =         "1999",
  editor =       "Peter J. Angeline and Zbyszek Michalewicz and 
                 Marc Schoenauer and Xin Yao and Ali Zalzala",
  volume =       "3",
  pages =        "1824--1840",
  address =      "Mayflower Hotel, Washington D.C., USA",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "6-9 " # jul,
  organisation = "Congress on Evolutionary Computation, IEEE / Neural
                 Networks Council, Evolutionary Programming Society,
                 Galesia, IEE",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, route and
                 network planning, agent evolution, connectionist
                 structures, distributed programs, evolutionary
                 strategies, genetically programmed networks, memory
                 mechanism, neural networks, rule based systems,
                 distributed programming, knowledge based systems,
                 neural nets, software agents",
  ISBN =         "0-7803-5536-9 (softbound)",
  ISBN =         "0-7803-5537-7 (Microfiche)",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1109/CEC.1999.785496",
  abstract =     "To achieve a high degree of autonomy, an agent usually
                 needs some kind of memory mechanism. We present a new
                 approach to the evolution of agents with memory, based
                 on the use of genetically programmed networks. These
                 are connectionist structures where each node has an
                 associated program, evolved using genetic programming.
                 Genetically programmed networks can easily be evolved
                 into agents with very different architectures. We
                 present experimental results from evolving genetically
                 programmed networks as neural networks, distributed
                 programs and rule based systems capable of solving
                 problems where the use of memory by the agent is
                 essential. Comparisons are made between the performance
                 of these solutions and the performance of solutions
                 obtained by other evolutionary strategies used to
                 evolve agents with memory",
  notes =        "CEC-99 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 Library of Congress Number = 99-61143",

Genetic Programming entries for Arlindo Ferreira da Silva Ana Paula Neves F Silva Ernesto Costa