• DocumentCode
    2007140
  • Title

    Distributed Planning in Stochastic Games with Communication

  • Author

    Burkov, Andriy ; Chaib-Draa, Brahim

  • Author_Institution
    DAMAS Lab., Laval Univ., Quebec City, QC, Canada
  • fYear
    2008
  • fDate
    11-13 Dec. 2008
  • Firstpage
    396
  • Lastpage
    401
  • Abstract
    This paper treats the problem of distributed planning in general-sum stochastic games with communication when the model is known. Our main contribution is a novel, game theoretic approach to the problem of distributed equilibrium computation and selection. We show theoretically and via experiments that our approach, when adopted by all agents, facilitates an efficient distributed equilibrium computation and leads to a unique equilibrium selection in general-sum stochastic games with communication.
  • Keywords
    distributed algorithms; planning (artificial intelligence); stochastic games; distributed equilibrium computation; distributed planning; stochastic game; Context modeling; Distributed computing; Game theory; Laboratories; Machine learning; Nash equilibrium; Process planning; Stochastic processes; Adaptive play; Game theory; Multiagent planning; Stochastic games;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-0-7695-3495-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2008.56
  • Filename
    4725004