基于模糊集合论的Agent联盟生成

Agent Coalition Generation Based on Fuzzy Set Theory

多Agent系统中联盟的生成是关键问题,主要研究如何在多Agent系统中构造面向任务的最优Agent联盟。对联盟生成问题作了新的描述,讨论了现有联盟生成方法的特点及不足,提出了一种基于模糊集合论的联盟生成方法。基于模糊集合论的隶属度概念,计算Agent对任务的隶属程度,并依据λ-截矩阵理论生成面向任务的Agent联盟,从而使任务由能力最适合的Agent组成的联盟来求解。实例分析说明了此方法的有效性。

In Multi-Agent System, the generation of agent coalition is a key topic. It mainly researches how to generate task-oriented optimal agent coalition. Describes the problem newly, discusses the characteristic and shortcomings of current methods, and proposes a novel method based on fuzzy set theory. Using the membership function, calculates the membership degree of an agent to a task as a value between 0 and 1, and then generates the task-oriented coalition by fuzzy clustering theory, so that the task can be performed by the most competent agent coalition. Moreover, an example is presented to illustrate the validity of the method.