• DocumentCode
    2565664
  • Title

    On oblivious equilibrium in large population stochastic games

  • Author

    Adlakha, Sachin ; Johari, Ramesh ; Weintraub, Gabriel Y. ; Goldsmith, Andrea

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
  • fYear
    2010
  • fDate
    15-17 Dec. 2010
  • Firstpage
    3117
  • Lastpage
    3124
  • Abstract
    We study stochastic games with a large number of players, where players are coupled via their payoff functions. A standard solution concept for such games is Markov perfect equilibrium (MPE). It is well known that the computation of MPE suffers from the “curse of dimensionality.” To deal with this complexity, several researchers have introduced the idea of oblivious equilibrium (OE). In OE, each player reacts to only the long-run average state of other players. In this paper, we study existence of OE, and also find conditions under which OE approximates MPE well.
  • Keywords
    Markov processes; stochastic games; Markov perfect equilibrium; oblivious equilibrium; payoff function; stochastic games; Approximation methods; Convergence; Equations; Games; Kernel; Markov processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2010 49th IEEE Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4244-7745-6
  • Type

    conf

  • DOI
    10.1109/CDC.2010.5717048
  • Filename
    5717048