Abstract
An average stochastic positional game is a stochastic game with average payoffs in which the set of states is divided into several disjoint subsets such that each subset represents the position set for one of the player and each player controls the Markov process only in his position set. In such a game each player chooses actions in his position set in order to maximize his average reward per transition. We show that an arbitrary average stochastic positional game possesses a stationary Nash equilibrium. Based on this result we propose an approach for determining the optimal stationary strategies of the players.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
