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一种基于P学习的分布式并行多任务分配算法

DOI: 10.3724/SP.J.1004.2011.00865, PP. 865-872

Keywords: 多Agent系统(MAS),并发多任务分配,联盟形成,P学习,协商

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Abstract:

?并行多任务分配是多agent系统中极具挑战性的课题,主要面向资源分配、灾害应急管理等应用需求,研究如何把一组待求解任务分配给相应的agent联盟去执行.本文提出了一种基于自组织、自学习agent的分布式并行多任务分配算法,该算法引入P学习设计了单agent寻找任务的学习模型,并给出了agent之间通信和协商策略.对比实验说明该算法不仅能快速寻找到每个任务的求解联盟,而且能明确给出联盟中各agent成员的实际资源承担量,从而可以为实际的控制和决策任务提供有价值的参考依据.

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