基于改进鹰鸽博弈的多智能体觅食协同算法

2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007) Pub Date : 2007-12-15 DOI:10.1109/CIS.WORKSHOPS.2007.119

Yuehai Wang, Jie Liu, Wei Meng

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引用次数: 4

摘要

多智能体觅食是验证不同协作算法有效性的常用基准。基于马尔可夫博弈的方法虽然不能为群体选择一致的均衡，但得到了广泛的应用。以进化稳定策略为最优解，建立了改进的鹰鸽博弈模型来模拟智能体之间的相互作用，并提出了一种思考-复制算法来寻找群体的一致最大奖励均衡。仿真结果验证了该算法的有效性。

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Cooperative Algorithm for Multi-agent Foraging Task Based on Modified Hawk-Dove Game

Multi-agent foraging is a popular benchmark to verify the effectiveness of different cooperation algorithm. Markov game based approaches were wildly used although they could not select consistent equilibrium for the group. Using evolutionarily stable strategy as optimal solution, we build a modified hawk-dove game model to simulate the interaction between agents, and then proposed a ponder-replicator algorithm to find certain consistent maximal reward equilibrium for the group. The simulation verified the efficiency of the proposed algorithm.

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2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)

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