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

机译:积雪演化博弈模型的多主体合作: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:合作通常被认为是关键且不清楚的概念之一,它使多代理系统与其他相关领域(例如分布式计算)有所区别。验证各种合作算法有效性的流行基准之一是多主体搜寻任务。尽管不能为组选择一致的均衡,但已提出了多种方法,其中广泛使用基于马尔可夫博弈的方法。本文提出了一种基于进化博弈的方法。在这种方法中,通过雪堆博弈对代理之间的交互进行建模,以发展进化稳定策略(ESS),并为该组代理带来最大的回报。仿真结果验证了所提算法的有效性。

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