• DocumentCode
    728564
  • Title

    ε-Nash equilibria for a partially observed mean field game with major player

  • Author

    Sen, Nevroz ; Caines, Peter E.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
  • fYear
    2015
  • fDate
    1-3 July 2015
  • Firstpage
    4791
  • Lastpage
    4797
  • Abstract
    Consider a dynamic game with a population of N minor agents, where N is very large, and a major agent where the agents are coupled in their nonlinear dynamics and cost functions such that even asymptotically as the population size goes to infinity the major agent has a non-vanishing effect on the minor agents. Such games are referred to as mean field games with major-minor agents (MM-MFG) and for MM-MFG, it has been demonstrated the mean field term is stochastic and the best response control actions of the minor agents depend on the state of the major agent as well as this stochastic mean field. In practical applications one is led to consider the situation where the minor agents partially observe (PO) the state of the major agent. In this work, we consider a restricted case of this scenario and demonstrate that in the case the minor agents are coupled to the major agent only through their cost functions, one can obtain the ε-Nash equilibrium property for the PO-MM-MFG best response control actions as the population size N goes to infinity.
  • Keywords
    stochastic games; ε-Nash equilibrium property; PO-MM-MFG best response control; cost functions; dynamic game; major player; major-minor agents; nonlinear dynamics; nonvanishing effect; partially-observed mean field game; population size; stochastic mean field term; Cost function; Games; Mathematical model; Process control; Sociology; Standards; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2015
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-1-4799-8685-9
  • Type

    conf

  • DOI
    10.1109/ACC.2015.7172084
  • Filename
    7172084