Hidden Markov Bayesian Game with Application to Chinese Education Game
Tóm tắt
In real game situations, players are often not perfectly informed about true states but can observe signals, and decision-making may involve several periods. In order to formulate such situations, this paper uses a hidden Markov model to describe the state process, thus introducing a repeated game with hidden Markovian states, called hidden Markov Bayesian game. For the new model, a notion of Nash equilibrium is presented and an algorithm is developed to facilitate obtaining the equilibrium quickly. An analysis of the Chinese education game shows that the observed signals play an important role in analyzing players’ behavior.
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