Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)
- 1997.11a
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- Pages.120-123
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- 1997
Fuzzy Inferdence-based Reinforcement Learning for Recurrent Neural Network
퍼지 추론에 의한 리커런트 뉴럴 네트워크 강화학습
Abstract
In this paper, we propose the Fuzzy Inference-based Reinforcement Learning Algorithm. We offer more similar learning scheme to the psychological learning of the higher animal's including human, by using Fuzzy Inference in Reinforcement Learning. The proposed method follows the way linguistic and conceptional expression have an effect on human's behavior by reasoning reinforcement based on fuzzy rule. The intervals of fuzzy membership functions are found optimally by genetic algorithms. And using Recurrent state is considered to make an action in dynamical environment. We show the validity of the proposed learning algorithm by applying to the inverted pendulum control problem.
Keywords
- Fuzzy Inference;
- Reinforcement Learning Associative Search Unit;
- Genetic Algorithm;
- Recurrent Neural Network