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The Multi-agent Learning Model Based on dynamic fuzzy logic

通讯和计算机（中英文版） 2006年第3期3卷 87-99页

作者： Liping Xie Fanzhang Li School of Computer Science and Technology Soochow University. Suzhou 215006. China

Machine Learning is one of the key problems of Artificial Intelligence, and the agent learning has become an important branch of machine learning. One of the main characters of intelligent agent is that it can adapt to the unknown environment. The ability to learn is the key property of agent. Because the learning act of agent is dynamic and fuzzy, this paper uses the conception of dynamic fuzzy logic (DFL)[1]. Based on DFL, this paper first presents two single-agent learning algorithms, namely, single-agent leaning algorithm based on DFL with immediate reward and single-agent learning algorithm based on DFL with mediate reward. Then the paper gives a multi-agent learning model based on DFL, namely a multi-agent learning model planned on a whole. Furthermore, this paper validates that the model is useful by an example.

关键词： dynamic fuzzy logic Agent Learning Machine Learning

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A dynamic fuzzy Description logic

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Wuhan University Journal of Natural Sciences 2008年第4期13卷 417-420页

作者： FANG Wei XIAN Xuefeng ZHAO Pengpeng CUI Zhiming Jiangsu Provincial Key Laboratory of Computer InformationProcessing Technology Soochow University Suzhou 215006Jiangsu China

fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuzzy extension of Attribute Language with Complement based on dynamic fuzzy logic called the dynamic fuzzy description logic （DFALC） is presented. The syntax and semantics of DFALC are formally defined, and the forms of axioms and assertions are specified. The DFALC provides more reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using fuzzy description logic FALC to act as logical foundation for the semantic Web. The extended DFALC is more expressive than the existing fuzzy description logics and present more fuzzy information on the semantic Web.

关键词： dynamic fuzzy logic description logic dynamic fuzzy description logic semantic Web

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A dynamic fuzzy Multi-attribute Group Decision Making Method for Supplier Evaluation and Selection

A Dynamic Fuzzy Multi-attribute Group Decision Making Method...

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第26届中国控制与决策会议

作者： Ruirui Bai Fanzhang Li Jiwen Yang College of Computer Science and Technology Soochow University

ISBN: (纸本)9781479937097

There are two key activities for an effective supply chain, one of which is the supplier evaluation and the other one is the supplier selection. In this paper, focusing on the dynamic fuzzy problems involved in the process of the supplier evaluation and selection, we proposed a dynamic fuzzy multi-attribute group decision making new ***, we would fully describe the decision-making information by employing dynamic fuzzy evaluation matrix,and get the best supplier by utilizing the ordered entropy weights. Experimental results on a practical supplier case show that the new model proposed here can not only effectively solve the problems of supplier evaluation and selection but also work better than the TOPSIS method.

关键词： dynamic fuzzy logic supplier evaluation and selection supply chain management multi-attribute group decision making

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