Fuzzy Fitted Q

In recent years a number of different algorithms have been applied to learning robot control [1], [2], [3]. One family of methods, Fitted value iteration methods [4], are particularly promising because of their data efficiency, a valuable capability in real world problems [5]. This paper proposes a...

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Bibliographic Details
Main Author: Gordon, S. W.
Format: Conference Proceeding
Language:English
Subjects:
Aerospace electronics
Educational institutions
Function approximation
Fuzzy logic
Learning (artificial intelligence)
Robots
Training
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Summary:In recent years a number of different algorithms have been applied to learning robot control [1], [2], [3]. One family of methods, Fitted value iteration methods [4], are particularly promising because of their data efficiency, a valuable capability in real world problems [5]. This paper proposes a variation of Fitted value iteration that uses Q-learning with fuzzy logic based function approximation [6]. We demonstrate the viability of this algorithm in simulation and in real world experiments.