摘要
针对N人非合作博弈Nash均衡求解问题,将免疫算法中抗体浓度抑制机制和免疫记忆功能引入基本粒子群算法,提出了一种求解博弈问题Nash均衡的免疫粒子群算法。该算法通过抗体浓度抑制机制和免疫记忆功能来保持种群的多样性,不仅保持了粒子群算法简单、易于实现的特点,而且增强了粒子群算法的全局寻优能力,加快了算法的速度。实验表明,提出的算法具有较好的性能,优于免疫算法和基本粒子群算法。
This paper involved the antibody concentration inhibition mechanism and immune memory function of immune algorithm into the original swarm algorithm,and proposed an immune particle swarm algorithm for solving Nash equilibrium of N-persons＇ non-cooperative game.The proposed algorithm had not only the properties of the original swarm algorithm,but also improved the abilities of seeking the global optimization result and evolution speed.The computer simulation results demonstrate that the proposed algorithm is effective,and it is superior to the immune algorithm and original swarm algorithm.
出处
《计算机应用研究》
CSCD
北大核心
2012年第1期28-31,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(70661001)
贵州大学青年基金资助项目(2010021)
关键词
免疫算法
粒子群算法
非合作博弈
纳什均衡
immune algorithm
particle swarm algorithm
non-cooperative game
Nash equilibrium
