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Search of Nash Equilibrium in Quadratic n-person Game

机译:二次n人游戏中纳什均衡的搜索。

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This paper is devoted to Nash equilibrium search in quadratic n-person game, where payoff function of each player is quadratic with respect to its strategic variable. Interactions between players are defined by corresponding bilinear terms in the payoffs. First, the statement is considered without any assumptions on payoffs' concavity. We use Nikaido-Isoda approach in order to reduce Nash equilibrium problem to optimization problem with nonconvex implicitly defined objective function. We propose global search algorithm based on the linearization of implicit part of the objective by linear support minorants. This technique allows to determine numerically whether the game has no equilibria. Then payoffs are assumed to be concave with respect to its strategic variables, and we suggest d.c. decomposition of the objective, thus corresponding local search method is applicable. Computational results are provided in the paper. Local search method is compared with extragradient equilibrium search algorithm.
机译:本文致力于二次n人游戏中的纳什均衡搜索,其中每个玩家的收益函数关于其战略变量都是二次的。玩家之间的互动由回报中相应的双线性项定义。首先,该声明在不考虑收益的凹性的情况下被考虑。我们使用Nikaido-Isoda方法将具有非凸隐式定义目标函数的Nash平衡问题简化为优化问题。我们提出了基于线性支持次要对象对目标的隐式部分进行线性化的全局搜索算法。该技术允许从数字上确定游戏是否没有平衡。然后假定收益相对于其战略变量而言是凹入的,我们建议使用直流电。分解目标,因此适用相应的局部搜索方法。本文提供了计算结果。将局部搜索方法与超梯度均衡搜索算法进行了比较。

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