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An Integrated Fuzzy Logic System in A Partially Known Environment

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Title
An Integrated Fuzzy Logic System in A Partially Known Environment
Author
Shin, Kyuyeol
Advisor
Bien, Zeungnam
Issue Date
2013-02
Publisher
Graduate School of UNIST
Abstract
In this thesis, we deal with a learning method for mimicking human behaviors in a partially known environment. Humans are possible to infer the appropriate action based on the partially known information to achieve their goals. The fuzzy logic is able to deal with a process of human reasoning by describing IF-THEN rules. The FQL method which is one of the reinforcement learning methods uses fuzzy logic for decision making. FQL is possible to expect improvement of the learning efficiency rather than ordinary Q-Learning method by using fuzzy logic. However, the problem comes from a conclusion part of FQL. The conclusion part of FQL consists of a set of singleton values. The behaviors of the agent are influenced by the number of singleton values. Especially, it is hart to expect the efficiency of learning when the environment is complex and a precise behavior is required. So, we suggest an integrated fuzzy logic system which is FQL with ANFIS.
Description
Electrical Engineering
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ECE_Theses_Master
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