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一种基于P学习的分布式并行多任务分配算法

苏兆品 蒋建国 梁昌勇 张国富

苏兆品, 蒋建国, 梁昌勇, 张国富. 一种基于P学习的分布式并行多任务分配算法. 自动化学报, 2011, 37(7): 865-872. doi: 10.3724/SP.J.1004.2011.00865
引用本文: 苏兆品, 蒋建国, 梁昌勇, 张国富. 一种基于P学习的分布式并行多任务分配算法. 自动化学报, 2011, 37(7): 865-872. doi: 10.3724/SP.J.1004.2011.00865
SU Zhao-Pin, JIANG Jian-Guo, LIANG Chang-Yong, ZHANG Guo-Fu. A Distributed Algorithm for Parallel Multi-task Allocation Based on Profit Sharing Learning. ACTA AUTOMATICA SINICA, 2011, 37(7): 865-872. doi: 10.3724/SP.J.1004.2011.00865
Citation: SU Zhao-Pin, JIANG Jian-Guo, LIANG Chang-Yong, ZHANG Guo-Fu. A Distributed Algorithm for Parallel Multi-task Allocation Based on Profit Sharing Learning. ACTA AUTOMATICA SINICA, 2011, 37(7): 865-872. doi: 10.3724/SP.J.1004.2011.00865

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

A Distributed Algorithm for Parallel Multi-task Allocation Based on Profit Sharing Learning

  • 摘要: 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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出版历程
  • 收稿日期:  2010-03-05
  • 修回日期:  2011-03-02
  • 刊出日期:  2011-07-20

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