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Multi-agent Cooperation Using Snow-Drift Evolutionary Game Model: Case Study in Foraging Task

机译:使用雪漂进化游戏模型的多功能协作:觅食任务的案例研究

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Cooperation is often considered as one of the key and unclear concepts, which differentiates multi-agent systems from other related fields such as distributed computing. One of the popular benchmarks for the verification of the effectiveness of various cooperation algorithms is multi-agent foraging task. Different approaches have been proposed among which Markov game based ones are widely used, though they could not select consistent equilibrium for the group. In this paper, an evolutionary game based method is proposed. In this method, the interactions among the agents are modeled by snow-drift game to evolve the evolutionary stable strategy (ESS) and bring the maximal reward for the group of agents. The simulation verified the efficiency of the proposed algorithm.
机译:合作通常被视为关键和不明确的概念之一,它将多种子体系统与分布式计算等其他相关领域的区别分享。验证各种合作算法的有效性的流行基准之一是多智能体觅食任务。已经提出了不同的方法,其中基于马尔可夫游戏的广泛使用,尽管它们无法为该组选择一致的均衡。本文提出了一种基于进化的游戏方法。在该方法中,代理商之间的相互作用由雪漂游戏进行建模,以发展进化稳定的策略(ESS),并为该组代理商带来最大奖励。该模拟验证了所提出的算法的效率。

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