LP Formulations of Two-Player Zero-Sum Stochastic Bayesian Finite Horizon Games
Nabiha Nasir Orpa, Lichun Li
Abstract
Nabiha Nasir Orpa, Lichun Li
Abstract
This paper studies two-player zero-sum stochastic Bayesian games where each player has its own dynamic state that is unknown to the other player. Using typical techniques, we provide the recursive formulas and the sufficient statistics in both the primal game and its dual games. It's also shown that with a specific initial parameter, the optimal strategy of one player in a dual game is also the optimal strategy of the player in the primal game. We, then, construct linear programs to compute the optimal strategies in both the primal game and the dual games and the special initial parameters in the dual games. The main results are demonstrated in a security problem of underwater sensor networks.
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This paper studies two-player zero-sum stochastic Bayesian games where each player has its own dynamic state that is unknown to the other player. Using typical techniques, we provide the recursive formulas and the sufficient statistics in both the primal game and its dual games. It's also shown that with a specific initial parameter, the optimal strategy of one player in a dual game is also the optimal strategy of the player in the primal game. We, then, construct linear programs to compute the optimal strategies in both the primal game and the dual games and the special initial parameters in the dual games. The main results are demonstrated in a security problem of underwater sensor networks.
Key concepts: Bayesian game, Sequential game, Zero-sum game, Dual (grammatical number), Zero (linguistics), Computer science, Mathematical optimization, Construct (python library)