论文标题
LP在有限的地平线两者零和随机贝叶斯游戏的有限地平线上的足够基于统计策略的表述
LP Formulations of sufficient statistic based strategies in Finite Horizon Two-Player Zero-Sum Stochastic Bayesian games
论文作者
论文摘要
本文研究了两个玩家零和随机贝叶斯游戏，每个玩家都有自己的动态状态，而另一个玩家不知道。使用典型的技术，我们在原始游戏及其双重游戏中提供了递归公式和足够的统计数据。还表明，有了特定的初始参数，双游戏中一个玩家的最佳策略也是原始游戏中玩家的最佳策略。为了处理长期有限的贝叶斯游戏，我们提供了一种算法来逐步计算玩家的次优策略，以避免LP复杂性。为此，我们计算了LPS在双游戏中找到特殊的初始参数，并更新双游戏的足够统计信息。绩效分析为最佳和次优策略之间的性能差异提供了上限。水下传感器网络的安全问题证明了主要结果。
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 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. To deal with the long finite Bayesian game we have provided an algorithm to compute the sub-optimal strategies of the players step by step to avoid the LP complexity. For this, we computed LPs to find the special initial parameters in the dual games and update the sufficient statistics of the dual games. The performance analysis has provided an upper bound on the performance difference between the optimal and suboptimal strategies. The main results are demonstrated in a security problem of underwater sensor networks.
