Title :
Adaptive Fuzzy Control with Reinforcement Learning
Author :
Berenji, Hamid R. ; Khedkar, Pratap S.
Author_Institution :
Sterling Software; AI Research Branch, MS: 269-2, NASA Ames Research Center, Mountain View, CA 94035. berenji@ptolemy.arc.nasa.gov
Abstract :
Non-adaptive fuzzy logic controllers can become adaptive by learning from experience in the framework of reinforcement learning. In this paper, we discuss fuzzy reinforcement learning as a hybrid approach which provides a unified framework for including two types of prior knowledge: knowledge for control action selection and knowledge for performance evaluation. We describe GARIC, an architecture for combining fuzzy logic control and reinforcement learning, and apply it to cart-pole balancing and the Space Shuttle attitude control.
Keywords :
Adaptive control; Artificial intelligence; Automatic control; Fuzzy control; Fuzzy logic; NASA; Programmable control; Regression analysis; Space shuttles; Supervised learning;
Conference_Titel :
American Control Conference, 1993
Conference_Location :
San Francisco, CA, USA
Print_ISBN :
0-7803-0860-3