基于纳什均衡保存的档案共享协同进化算法

Haoyang Chen, Yasukuni Mori, I. Matsuba
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引用次数: 0

摘要

协作协同进化算法(CCEA)被广泛应用于解决大规模和复杂的问题,与传统的遗传算法相比具有显著的速度提升。然而,由于其合作性质,CCEA并不寻求最优解决方案,而是寻求折衷解决方案。因此,在目标问题具有无限纳什均衡的情况下,即使使用共享存档,CCEA也有望收敛到次优解。在本文中,我们提出了一种纳什均衡保存策略,使CCEA能够跳出次优解并继续搜索,而不会陷入到目前为止找到的相同次优解中。实验结果表明,本文提出的策略提高了档案共享CCEA算法的性能,特别是在处理具有无限纳什均衡的问题方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Archive-shared cooperative coevolutionary algorithm using Nash equilibria preservation
Cooperative Coevolutionary Algorithm (CCEA) has been widely applied to solve large scale and complex problems, which result in significant speedups over traditional genetic algorithm. However, CCEA do not search for the optimal solutions but the compromised solutions because of its nature of cooperation. So in the case that the object problem has infinite Nash equilibria, CCEA is expected to converge into suboptimal solution even employing the shared archive. In this paper, we propose a Nash equilibria preservation strategy which enables CCEA to jump out of the suboptimal solution and to keep searching without falling into the same suboptimal solutions found so far. The experiment results show that the capability of the archive-shared CCEA has been improved by using the proposed strategy, especially in dealing with problem having infinite Nash equilibria.
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