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A fuzzy integral based query dispatching model in collaborative case-based reasoning

机译:协同案例推理中基于模糊积分的查询调度模型

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摘要

In a collaborative (distributed) Case-Based Reasoning (CBR) environment, an input query case could be compared with the old cases that are resided in many different CBR agents in the network. How to obtain the best solution effectively and efficiently from this distributed CBR network depends on a carefully designed query dispatching strategy. In this paper, we propose a fuzzy integral based approach to measure the competence of different CBR agents in the network and suggest three query dispatching policies which could be used to fulfill this task. They are: To-Top policy, Strong-Strong policy and Best-Committee policy. The experimental result shows that our proposed policies are comparatively better than the existing ones developed by Plaza and Ontanon.
机译:在协作(分布式)基于案例的推理(CBR)环境中,可以将输入查询案例与网络中许多不同CBR代理中驻留的旧案例进行比较。如何从该分布式CBR网络中有效,高效地获得最佳解决方案,取决于精心设计的查询调度策略。在本文中,我们提出了一种基于模糊积分的方法来衡量网络中不同CBR代理的能力,并提出了三种可用于完成此任务的查询调度策略。它们是:最高政策,强政策和最佳委员会政策。实验结果表明,我们提出的政策相对于Plaza和Ontanon制定的现有政策更好。

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