[1]蒋伟进,骆 菲,史德嘉.MAS动态协作任务求解模型与算法[J].智能系统学报,2010,5(02):161-168.
 JIANG Wei-jin,LUO Fei,SHI De-jia.Modeling and solving dynamic collaborative tasks in a multiAgent system[J].CAAI Transactions on Intelligent Systems,2010,5(02):161-168.
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第5卷
期数:
2010年02期
页码:
161-168
栏目:
出版日期:
2010-04-25

文章信息/Info

Title:
Modeling and solving dynamic collaborative tasks in a multiAgent system
文章编号:
1673-4785(2010)02-0161-08
作者:
蒋伟进12骆 菲2史德嘉1
1.湖南商学院 计算机应用研究所,湖南 长沙 410205;
 2.湘潭大学 信息工程学院,湖南 湘潭 4110006
Author(s):
JIANG Wei-jin12 LUO Fei1 SHI De-jia1
1.School of Computer, Hunan University of Commerce, Changsha 410205,China;
2.School of Information Engineering, Xiangtan University, Xiangtan 411006,China
关键词:
资源优化调度动态协作博弈计算MAS
Keywords:
resource allocation modeldynamic collaboationgame compute multiAgent system (MAS)
分类号:
TP393; TP311
文献标志码:
A
摘要:
针对网格环境的自治性、动态性、分布性和异构性等特征.提出基于多智能体系统(mutil agent system, MAS) 博弈协作的资源动态分配和任务调度模型,建立了能够反映供求关系的网格资源调度动态任务求解算法,证明了资源分配博弈中Nash均衡点的存在性、惟一性和Nash均衡解.该方法能够利用消费者Agent的学习和协商能力,引入消费者的心理行为,使消费者的资源申请和任务调度具有较高的合理性和有效性.实验结果表明,该方法在响应时间的平滑性、吞吐率及任务求解效率方面比传统算法要好,从而使得整个资源供需合理、满足用户QoS要求.
Abstract:
A grid environment is characterized by its autonomy, its dynamic properties, its distributive properties, and its heterogeneity. We proposed a model for dynamic resource distribution and task scheduling based on a multiagent system (MAS) collaborative game. An algorithm for dynamically solving task scheduling of grid resources was developed. It reflected actual relationships between supply and demand. The existence and uniqueness of a Nash equilibrium point in the resource distribution game was proven, and then the Nash equilibrium solution presented. The proposed method can make full use of the learning and negotiating abilities of consumer agents and also introduces psychologically driven behavior. In this way the resource application and task scheduling of consumers became more reasonable and effective. Experimental results demonstrated that this approach improves smoothness, throughput capacity and task solving efficiency compared to traditional methods. Supply and demand became more manageable, meeting the requirements of quality of service (QoS).

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备注/Memo

备注/Memo:
收稿日期:2009-12-20.
基金项目:
湖南省自然科学基金重点资助项目(06JJ2033);
湖南省社会科学基金资助项目(07YBB239).
通信作者:蒋伟进.E-mail: jlwxjh@163.com.
作者简介:
蒋伟进,男,1964年生,教授,CCF高级会员,主要研究领域为智能计算、Agent计算、复杂自适应系统.发表学术论文30余篇.获省市科技奖励10项.
骆 菲,男,1986年生,硕士研究生, 主要研究方向为Agent计算、智能决策与方法、复杂系统建模.
史德嘉,女,1963年生,教授.主要研究方向分布式人工智能、多主体系统、智能控制.主持国家科技部、省级重点项目2项. 发表学术论文20余篇,被EI检索10篇.
更新日期/Last Update: 2010-05-24