摘要
多Agent协作过程中的许多问题都可在分布式约束优化问题(DCOP)框架下建模,但多局限于规划问题,且一般需Agent具有完全、准确收益函数.针对DCOP局限性,定义动态分布式约束优化问题(DDCOP),分析求解它的两个关键操作:Exploration和Exploitation,提出基于混沌蚂蚁的DDCOP协同求解算法(CA-DDCOP).该算法借鉴单只蚂蚁的混沌行为和蚁群的自组织行为,实现Exploration和Exploitation,根据玻尔兹曼分布,建立平衡Exploration和Exploitation的协同方法.通过多射频多信道无线Ad Hoc网络的信道分配验证该算法的有效性.
A large number of problems in the muhiagent collaboration process can be modeled under the framework of distributed constraint optimization problem （DCOP）. However, DCOP framework is limited to the issue of planning, and the agents in DCOP generally require a complete and accurate reward function. To resolve this issue, a dynamic distributed constraint optimization problem （DDCOP） is defined, and DDCOP＇s crucial operations, exploration and exploitation, are analyzed. Furthermore, a chaotic ant based collaborative solving algorithm for dynamic distributed constraint optimization problem （CA-DDCOP） is proposed. The CA-DDCOP algorithm single ant and self-organizing behavior of ant colony, is established based on chaotic behavior of a thereby the exploration and exploitation arerealized. The proposed algorithm achieves the collaboration of exploration and exploitation according to the Bohzmann distribution. Then a channel allocation in multi-radio multi-channel Ad Hoc networks is solved by the CA-DDCOP algorithm. The simulation results show that the CA-DDCOP algorithm performs effectively.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2013年第9期801-811,共11页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.61070220,60873195)
高等学校博士学科点专项科研基金项目(No.20090111110002)
全国博士学位论文作者专项资金项目(No.200951)
安徽高校省级自然科学研究重点项目(No.KJ2013A229)资助
关键词
混沌
协同求解
动态分布式约束优化
信道分配
Chaos, Collaborative Solving, Dynamic Distributed Constraint Optimization, ChannelAllocation
