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A Multi-Modal Coevolutionary Algorithm for Finding All Nash Equilibria of a Multi-Player Normal Form Game

机译:一种多模态共耦合算法,用于查找多次播放器正常形式游戏的所有纳什均衡

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Nash's theorem says that every game that has a finite strategic form has at least one Nash point. The problem of finding one Nash point is a well studied problem, and there exist a number of different methods for numerically computing a sample Nash equilibrium. But the problem of finding all equilibria has been addressed only recently. Literature review shows that many of the existing methods for detecting all equilibria are computationally intensive and error prone. In this paper we present a multi-modal coevolutionary algorithm that is able to detect all Nash points of a multi-player normal form game at the same time. We formulate the problem of solving a matrix game as a multi- modal optimization problem. Then a coevolutionary algorithm decomposes the problem and solves it in a parallel form. It associates one population to each player's strategies. So various components of the problem will coevolve and better results may be produced at lower computational costs.
机译:NASH的定理表明,每个有限的战略形式的游戏至少有一个纳什点。找到一个桡皑点的问题是研究了良好的问题,并且存在许多不同的方法用于数值计算样品纳什均衡。但最近才解决了寻找所有均衡的问题。文献综述表明,许多用于检测所有均衡的现有方法都是计算密集的,并且容易出错。在本文中,我们提出了一种多模态共聚合算法,其能够同时检测多玩家正常形式游戏的所有NASH点。我们制定解决矩阵游戏作为多模态优化问题的问题。然后,共乐算法将问题分解并以并行形式解决它。它将一个人们与每个玩家的策略联系起来。因此,问题的各种组成部分将共同,并且可以以较低的计算成本产生更好的结果。

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