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- W2377616739 abstract "To overcome the problems of getting perfect fuzzy navigation control rules under complicated unknown environment and learning in the continuous state space and continuous action space of traditional reinforcement learning algorithms,a fuzzy reinforcement learning algorithm was proposed. We design a fuzzy reinforcement learning system by combining fuzzy inference system and reinforcement learning algorithms. On the one hand,using Sarsa(λ)-learning algorithm to obtain fuzzy rule base of the fuzzy logic controller when lack of expert experience. On the other hand,It can go through every pair of state and action for robot by using widely approximation speciality of fuzzy inference system. At the same time,learning speed due to the introduction of limited expert experience that make Sarsa(λ)-learning have some prior knowledge. Simulation experiments indicates the good real-time and robustness of the proposed approach that can efficiency solve the navigation problem of mobile robot under the unknown complicated environment." @default.
- W2377616739 created "2016-06-24" @default.
- W2377616739 creator A5012336954 @default.
- W2377616739 date "2013-01-01" @default.
- W2377616739 modified "2023-09-25" @default.
- W2377616739 title "Navigation Research of a Mobile Robot with Fuzzy Sarsa(λ) Learning" @default.
- W2377616739 hasPublicationYear "2013" @default.
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