Deriving and Analysing Optimal Strategies in Bayesian Models of Games
通过图形化方法识别重复贝叶斯博弈的最优解形式，并以囚徒困境为例，增强Wilson算法以得出显式最优策略，同时利用贝叶斯理性讨论对手反应模型的现实性。
Wilson (1986) gives a backwards induction algorithm for sequentially obtaining the optimal next move in a repeated Bayesian game. In this paper we show how to identify the form of an optimal solution of such a game by a graphical procedure. By means of the Prisoner's Dilemma game, we illustrate how Wilson's algorithm can be enhanced using the derived analytic form of the solution to produce an explicit optimal strategy. We can then determine not only how P 1 should play on all subsequent moves of the game, but also use ideas of Bayes rationality to discuss whether a given model of P 2 's reactions is realistic.