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    Agent组织规则的再励学习

    Agent Organization Rule Generation Based on Reinforcement Learning

    • 摘要: Agent组织是一种灵活有效的多Agent系统求解方式 Agent组织规则在Agent组织的求解过程中起着重要作用 ,可以有效地减少冲突提高求解效率 给出了一种基于再励学习的Agent组织规则生成机制和相应的算法 ,通过实验表明了算法的有效性 ,改进了Zambonelli和Jennings等人关于Agent组织规则的工作

       

      Abstract: Agent organization is a flexible and effective way of solving multi agent system problems Within an agent organization, the rule plays an important role for reducing conflicts and improving resolution efficiency In this paper, mechanisms and the associated algorithms of agent organization rule generation based on reinforcement learning are given The experiment shows that the algorithms are more effective than the normal method The agent organization rule generation method proposed improves the work conducted by Zambonelli and Jennings

       

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