论文标题
在多人游戏DAG结构的随机游戏中计算NASH平衡，并具有持久的不完美信息
Computing Nash Equilibria in Multiplayer DAG-Structured Stochastic Games with Persistent Imperfect Information
论文作者
论文摘要
许多重要的现实世界设置包含多个在未知持续时间与概率状态过渡的互动的玩家，并且自然地将其建模为随机游戏。关于随机游戏算法的先前研究重点是两人零和游戏，具有完美信息的游戏以及具有本地信息不完美的信息，并且在游戏状态之间不扩展。我们提出了一种算法，用于在多人游戏通用随机游戏中近似NASH平衡，并具有持久的不完美信息，可扩展整个游戏游戏。我们在4播放器不完美的海军战略规划方案中进行实验。使用新的过程，我们能够证明我们的算法计算了一种在此游戏中近似NASH平衡的策略。
Many important real-world settings contain multiple players interacting over an unknown duration with probabilistic state transitions, and are naturally modeled as stochastic games. Prior research on algorithms for stochastic games has focused on two-player zero-sum games, games with perfect information, and games with imperfect-information that is local and does not extend between game states. We present an algorithm for approximating Nash equilibrium in multiplayer general-sum stochastic games with persistent imperfect information that extends throughout game play. We experiment on a 4-player imperfect-information naval strategic planning scenario. Using a new procedure, we are able to demonstrate that our algorithm computes a strategy that closely approximates Nash equilibrium in this game.
