Reinforcement learning and tuning for neural network based fuzzy logic controller

被引：0
|
作者：
Wu, GF [1 ]
Sun, HJ [1 ]
Dong, JQ [1 ]
Cao, M [1 ]
Wang, T [1 ]
机构：
[1] Shanghai Univ, Sch Engn & Comp Sci, Shanghai 200072, Peoples R China
来源：
2000 5TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS I-III | 2000年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The paper proposes a Reinforcement Neural Network based fuzzy Logic Controller (RNNFLC) for solving reinforcement learning and tuning problems. A simplified and effective reinforcement based learning algorithm is proposed to generate fuzzy rules automatically. A reinforcement-tuning algorithm is introduced to tune the membership function. The RNNFLC is applied to a cart-pole balancing system and shows significant improvements.
引用
收藏
页码：1695 / 1700
页数：6
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