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    • Keywords


      Nash equilibria; Decentralised learning algorithm

    • Abstract


      This paper considers a multi-person discrete game with random payoffs. The distribution of the random payoff is unknown to the players and further none of the players know the strategies or the actual moves of other players. A class of absolutely expedient learning algorithms for the game based on a decentralised team of Learning Automata is presented. These algorithms correspond, in some sense, to rational behaviour on the part of the players. All stable stationary points of the algorithm are shown to be Nash equilibria for the game. It is also shown that under some additional constraints on the game, the team will always converge to a Nash equilibrium.

    • Author Affiliations


      V V Phansalkar1 P S Sastry1 M A L Thathachar1

      1. Department of Electrical Engineering, Indian Institute of Science, Bangalore - 560012, India
    • Dates

  • Proceedings – Mathematical Sciences | News

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      Posted on July 25, 2019

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