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Absolutely expedient algorithms for learning Nash equilibria

Phansalkar, VV and Sastry , PS and Thathachar, MAL (1944) Absolutely expedient algorithms for learning Nash equilibria. In: Proceedings of the Indian Academy of Sciences - Mathematical Sciences, 104 (1). pp. 279-294.

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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.

Item Type: Journal Article
Publication: Proceedings of the Indian Academy of Sciences - Mathematical Sciences
Publisher: Indian Academy of Sciences
Additional Information: Copyright of this article belongs to Indian Academy of Sciences.
Keywords: Nash equilibria;Decentralised learning algorithm.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 03 Jun 2011 07:51
Last Modified: 03 Jun 2011 07:51
URI: http://eprints.iisc.ac.in/id/eprint/36096

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