Title :
Refining linear fuzzy rules by reinforcement learning
Author :
Berenji, Hamid R. ; Khedkar, Pratap S. ; Malkani, Anil
Author_Institution :
Intelligent Inference Syst. Corp., NASA Ames Res. Center, Moffett Field, CA, USA
Abstract :
We present an algorithm that refines a set of linear fuzzy rules, which use ellipsoidal radial basis functions in their antecedents and have multiple linear outputs in their consequents (similar to TSK rules), using reinforcement learning. We show how this learning algorithm can be used to refine the performances of controllers for a typical cart-pole balancing system
Keywords :
fuzzy control; fuzzy set theory; fuzzy systems; inference mechanisms; knowledge based systems; learning (artificial intelligence); GARIC-RB algorithm; cart-pole balancing system; clustering; ellipsoidal radial basis functions; elliptical generalisation; fuzzy set theory; inference; linear fuzzy rules; reinforcement learning; Clustering algorithms; Computational intelligence; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Inference algorithms; Intelligent systems; Learning; NASA; Research and development;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.552634
