论文标题
用于计算连续游戏中近似NASH平衡的算法，并应用连续的blotto
Algorithm for Computing Approximate Nash Equilibrium in Continuous Games with Application to Continuous Blotto
论文作者
论文摘要
已经开发了成功的算法，用于计算各种有限的游戏类中的NASH平衡。但是，解决持续游戏（纯粹的战略空间（可能无限）无限）的持续游戏更具挑战性。尽管如此，许多现实世界中的许多现实领域都具有连续的动作空间，例如，行动是指自然被模型为实现的时间，金钱或其他资源，而不是集成不可或缺的。我们提出了一种新算法，用于{近似}连续游戏中的nash平衡策略。除了两人零和游戏外，我们的算法还适用于具有不完美信息的多人游戏和游戏。我们在连续的不完美信息游戏中尝试了算法，其中两个玩家在多个战场上分发资源。 Blotto Games经常被用来建模国家安全方案，并已应用于选举竞争和拍卖理论。实验表明，我们的算法能够快速计算该游戏的NASH平衡策略的近似值。
Successful algorithms have been developed for computing Nash equilibrium in a variety of finite game classes. However, solving continuous games -- in which the pure strategy space is (potentially uncountably) infinite -- is far more challenging. Nonetheless, many real-world domains have continuous action spaces, e.g., where actions refer to an amount of time, money, or other resource that is naturally modeled as being real-valued as opposed to integral. We present a new algorithm for {approximating} Nash equilibrium strategies in continuous games. In addition to two-player zero-sum games, our algorithm also applies to multiplayer games and games with imperfect information. We experiment with our algorithm on a continuous imperfect-information Blotto game, in which two players distribute resources over multiple battlefields. Blotto games have frequently been used to model national security scenarios and have also been applied to electoral competition and auction theory. Experiments show that our algorithm is able to quickly compute close approximations of Nash equilibrium strategies for this game.
