一种混合粒子群算法求解Nash平衡  

A Hybrid Particle Swarm Optimization for Solving Nash Equilibrium

作　　者：黎华琴 

机构地区：[1]贵州理工学院理学院,贵州 贵阳

出　　处：《计算机科学与应用》2020年第4期760-766,共7页Computer Science and Application

基　　金：贵州省教育厅青年科技人才成长项目(黔教合KY字[2017]225).

摘　　要：目前,已有多种智能算法应用于求解Nash平衡,这些算法各有优缺点,为避免粒子群算法在求解Nash平衡时陷入局部最优,本文将遗传算法中的杂交算子引入基本粒子群算法中,设计了一个求解博弈Nash平衡的混合粒子群算法。实验表明,设计的算法具有较好的性能,优于免疫算法,免疫粒子群算法与基本粒子群算法。At present, many intelligent algorithms have been used for solving the Nash equilibrium. They have their own advantages and disadvantages. To overcome local optimum, it designs a hybrid Particle Swarm Optimization for solving Nash equilibrium, by combining the crossover operator in Genetic Algorithm with the basic Particle Swarm Optimization. Experiments show that the algorithm designed is effective, and it is superior to the immune algorithm, immune Particle Swarm Optimization, and basic Particle Swarm Optimization.

关 键 词：NASH平衡 粒子群算法 杂交 混合 

分 类 号：O15[理学—数学]