| 协同免疫量子粒子群算法求非合作博弈Nash均衡解 |
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| 引用本文： | 刘露萍,贾文生,蔡江华.协同免疫量子粒子群算法求非合作博弈Nash均衡解[J].计算机应用与软件,2019(8):203-209. |
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| 作者姓名： | 刘露萍 贾文生 蔡江华 |
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| 作者单位： | 1.贵州大学数学与统计学院 |
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| 基金项目： | 国家自然科学基金项目(11561013);人社部留学归国人员择优资助项目(人社No.[2015]192);贵州省联合基金项目(黔科联合[2014]7643);贵州大学人才引进基金项目(贵大[2014]05) |
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| 摘 要： | 考虑n人非合作博弈Nash均衡求解问题。将混合策略意义下的Nash均衡转化为最优化问题;把免疫记忆、自我进化、信息共享机制加入量子粒子群算法,通过概率浓度选择公式来保持种群的多样性,提出协同免疫量子粒子群算法。4个经典的数值算例说明,该算法优于免疫粒子群算法,具有较强的寻优能力和收敛性能。
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| 关 键 词： | NASH均衡 概率浓度选择 量子粒子群算法 协同免疫量子粒子群算法 |
COEVOLUTIONARY IMMUNE QUANTUM PARTICAL SWARM OPTIMIZATION IN SOLVING NASH EQUILIBRIUM FOR NON-COOPERATIVE GAME |
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| Liu Luping,Jia Wensheng,Cai Jianghua.COEVOLUTIONARY IMMUNE QUANTUM PARTICAL SWARM OPTIMIZATION IN SOLVING NASH EQUILIBRIUM FOR NON-COOPERATIVE GAME[J].Computer Applications and Software,2019(8):203-209. |
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| Authors: | Liu Luping Jia Wensheng Cai Jianghua |
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| Affiliation: | (College of Mathematics and Statistics,Guizhou University,Guiyang 550025,Guizhou,China) |
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| Abstract: | Considering Nash equilibrium for N-persons non-cooperative game,Nash equilibrium problems of mixed strategy was converted to optimization problems.We introduced immune memory,self-evolution,information sharing regulation into quantum particle swarm optimization,and maintained the diversity of the population by probability density selection.Based on this,we proposed a coevolutionary immune quantum particle swarm optimization (CIQPSO).The four classical numerical examples show that CIQPSO is superior to the immune particle swarm optimization algorithm,and has stronger optimization ability and convergence performance. |
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| Keywords: | Nash equilibrium Probability density selection Quantum particle swarm optimization Coevolutionary immune quantum particle swarm optimization |
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