• DocumentCode
    3207695
  • Title

    Cooperative agents through bidding

  • Author

    Qi, Dehu ; Sun, Ron

  • Author_Institution
    Comput. Sci. Dept., Lamar Univ., Beaumont, TX, USA
  • fYear
    2004
  • fDate
    8-10 Nov. 2004
  • Firstpage
    444
  • Lastpage
    449
  • Abstract
    One of the main research topics in multiagent systems is learning cooperation among agents. This paper presents a multiagent reinforcement learning approach with bidding. Self-interested agents cooperate with each other through bidding and evolutionary computation. We tested the approach to the TSP problem. The experimental results show our approach can achieve a certain level of performance in problem solving.
  • Keywords
    evolutionary computation; learning (artificial intelligence); multi-agent systems; problem solving; travelling salesman problems; cooperative agent; evolutionary computation; multiagent system; problem solving; reinforcement learning; Cognitive science; Communication system control; Computer science; Evolutionary computation; Genetic algorithms; Learning; Multiagent systems; Problem-solving; Sun; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Reuse and Integration, 2004. IRI 2004. Proceedings of the 2004 IEEE International Conference on
  • Print_ISBN
    0-7803-8819-4
  • Type

    conf

  • DOI
    10.1109/IRI.2004.1431501
  • Filename
    1431501