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Reinforcement fuzzy control using Ant Colony Optimization

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2 Author(s)
Chia-Feng Juang ; Dept. of Electr. Eng., Nat. Chung Hsing Univ., Taichung ; Chun-Ming Lu

This paper proposes the design of a fuzzy controller by ant colony optimization (ACO) incorporated with fuzzy-Q learning, called ACO-FQ, with reinforcements. For a fuzzy controller, we list all candidate consequent control actions of each fuzzy rule. Each candidate in the consequent part of a rule is assigned with a corresponding Q-value. Searching for the best one among all combinations is partially based on pheromone trail and partially based on Q-values. To verify the performance of ACO-FQ, reinforcement fuzzy control of water bath temperature control system is simulated.

Published in:

Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on

Date of Conference:

12-15 Oct. 2008

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