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    贺利坚, 黄厚宽, 张 伟. 多Agent系统中信任和信誉系统研究综述[J]. 计算机研究与发展, 2008, 45(7).
    引用本文: 贺利坚, 黄厚宽, 张 伟. 多Agent系统中信任和信誉系统研究综述[J]. 计算机研究与发展, 2008, 45(7).
    He Lijian, Huang Houkuan, Zhang Wei. A Survey of Trust and Reputation Systems in Multi Agent Systems[J]. Journal of Computer Research and Development, 2008, 45(7).
    Citation: He Lijian, Huang Houkuan, Zhang Wei. A Survey of Trust and Reputation Systems in Multi Agent Systems[J]. Journal of Computer Research and Development, 2008, 45(7).

    多Agent系统中信任和信誉系统研究综述

    A Survey of Trust and Reputation Systems in Multi Agent Systems

    • 摘要: MAS环境同人类社会类似, 充斥着大量不确定因素,因此,在MAS环境中引入信任来解决合作与交互问题具有重要意义. 信任通常来源于直接信任和信誉两种途径,信誉系统是用于支持信任评价的机制. 信誉系统的研究范围分为个体层和系统层两个层次,信誉系统的研究工作更关注个体层,信任的评价要符合准确性等特点. 信誉系统中信任的表示一般采用基于认知观点和数值观点的方法. 信誉系统采用集中式、分布式和混合式3种体系结构,各种模型都需要明确信任表示、传播与汇总的方法. 目前两个较为成功的分布式多Agent信誉系统是ReGreT和FIRE. 信息不精确的问题是信誉系统中的基本问题,也是一个迫切需要深入研究的课题. 信誉系统研究中的一个突出问题是尚无公认的测试平台,Agent信誉和信任测试床(ART)项目作了有益的探索. 在上述评述的基础上,可以在新模型和机制的构建、现有模型改进和完善、测试平台的研究和开发等方面有待进一步开展工作.

       

      Abstract: It is of great importance to introduce trust when solving the collaboration and interaction problem in multi agent system (MAS) environment because like the human society, there are so many indeterminate factors in the MAS environment. Generally speaking, trust derives from direct trust and reputation, and the reputation system is the mechanism to support trust evaluation. The reputation system can be studied at both individual and system level, and more attention should be paid to the former. Whether cognitive view or numerical view is used to represent trust, the trust value evaluated by the reputation system should be accurate, adaptive, and so on. The reputation system can adopt concentrated, distributed or mixture architectures and they all demand the way to represent, propagate and aggregate the trust information. Up to now, the ReGreT and FIRE are both successful among the distributed architecture. As a hot, basic issue in the reputation system, inaccuracy information problem is a pressing topic, which requires to be explored further. Another limitation is that no reputation model test platform receives public recognition, even though the Agent Reputation and Trust (ART) Testbed Project has gained preliminary achievements. Based on the above introduction and review, it is proposed that more work should be done to construct a new model and mechanism, improve the existing models, and develop a new test platform.

       

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