Fuzzy epoch-incremental reinforcement learning algorithm

Authors:
Roman Zajdel
Affiliations:
Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, Rzeszow, Poland
Venue:
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Year:
2012

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Abstract

The new epoch-incremental reinforcement learning algorithm with fuzzy approximation of action-value function is developed. This algorithm is practically tested in the control of the mobile robot which realizes goal seeking behavior. The obtained results are compared with results of fuzzy version of reinforcement learning algorithms, such as Q(0)-learning, Q(λ )-learning, Dyna-learning and prioritized sweeping. The adaptation of the fuzzy approximator to the model based reinforcement learning algorithms is also proposed.