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CORE: A Trust Model for Agent Coalition Formation

机译:核心:Agent联盟形成的信任模型

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CORE, a trust model is proposed trying to solve agent coalition formation problem. The model characterizes an agentȁ9;s trust from two aspects of competence and reputation. In the paper, the Euclidean distance formula of vector space on competence field is used to measure the extent which an agent fitting for a particular task, and the membership function is used to characterize an agentȁ9;s reputation. At the begin of the task, appropriate agents are selected to form a coalition according to their trust value; in the process of the task, the agentȁ9;s competence gains and reputation updates; after completing the task, the model can renovate every agentȁ9;s trust according to their behavior during the coalition, which is viewed as an evidence for next task. Finally, the model is carried out by programming on the NetLogo platform.
机译:为了解决Agent联盟形成问题,提出了一种信任模型。该模型从能力和声誉两个方面描述了一个代理人的9信任。本文利用胜任力域上向量空间的欧几里德距离公式来衡量一个代理人适合某项任务的程度,并使用隶属度函数来描述一个代理人的声誉。在任务开始时,根据其信任值选择适当的代理以组成联盟。在任务执行过程中,代理人ȁ9;其能力获得和声誉更新;完成任务后,该模型可以根据联盟中每个特工的行为更新其9的信任,这可作为下一个任务的证据。最后,通过在NetLogo平台上编程来执行该模型。

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