基于社区发现的多主体信任评估

为了解决多主体系统(MAS)的开放性、动态性和不确定性所带来的主体信任问题，提出一种基于社区发现的信任评估方法。首先使用G-N算法(GIRVAN M, NEWMAN M E J. Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(12):7821-7826)发现系统中的社区结构；然后根据推荐主体的推荐信任分别计算被评估主体的社区内部、外部声誉，进而结合直接信任形成主体的综合信任度；最后根据协作反馈实现主体信任度的动态调整。仿真实验结果表明，基于社区发现的信任评估方法能有效评估主体信任度，通过引入反馈机制能进一步提高交互成功率。

Trust evaluation based on community discovery in multi-Agent system

To solve the trust problem among Agents brought about by the characteristics of openness, dynamics and uncertainty of Multi-Agent System (MAS), a method for trust evaluation based on community discovery was proposed. Firstly, the G-N algorithm (GIRVAN M, NEWMAN M E J. Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(12): 7821-7826) was employed to discover the community structure in the system. Both the inner and outer community reputations of the estimated Agents were calculated respectively by use of the belief of the recommending Agents, and then the total trust value was further assessed by combining the reputations and the direct trust values. Furthermore, the dynamic adjustment of Agent's trust value was realized via cooperation feedback. Lastly, the simulation results show that the community discovery-based trust evaluation method can effectively evaluate the Agent's trust value, and further enhance the ratio of successful interactions with the introduction of the feedback mechanism.