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Accuracy based fuzzy Q-learning for robot behaviours

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2 Author(s)
Dongbing Gu ; Dept. of Comput. Sci., Essex Univ., Colchester, UK ; Huosheng Hu

This work presents a learning approach to fuzzy classifier systems. Q-learning algorithm is employed to implement credit assignment of the learning. GA operators are used as an action selection mechanism of the learning. The learning approaches can be viewed as a fuzzy learning classifier system or a Q-learning algorithm that adopts fuzzy logic to generalise Q-learning results. Rule accuracies are treated as rule fitness values. The learning algorithm is applied to a control robot behaviour.

Published in:

Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on  (Volume:3 )

Date of Conference:

25-29 July 2004