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引用次数: 1
摘要
在泛在环境中，多个智能体动态地相互协作。因此，有效地对其特征进行建模并进行分类是非常重要的。本文提出了一种基于供方/需方模型的智能体建模和分组方法。Agent之间的匹配程度由UoP (Utility of Predicate)、UoA (Utility of Agent)和UoC (Utility of Community)来建模。实验表明，与随机分组相比，该方案显著减少了无用数据流和代理间通信。
A new agent characterization model and grouping method for multi-agent system
In ubiquitous environment a number of agents dynamically collaborate with each other. Therefore, it is very important to effectively model their characteristics and group them accordingly. In this paper we introduce a new agent modeling and grouping method based on the supplier/demander model. The degree of matching between the agents is modeled by UoP (Utility of Predicate), UoA (Utility of Agent), and UoC (Utility of Community). An experiment reveals that the proposed scheme drastically decreases useless data stream and inter-broker communications compared to random grouping.
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