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|Title:||FUZZY INFERENCE SYSTEMS OPTIMIZATION BY REINFORCEMENT LEARNING|
HADJILI, M. L
fuzzy inference systems
|Abstract:||Fuzzy rules for control can be effectively tuned via reinforcement learning. Reinforcement learning is a weak learning method wich only requires information on the succes or failure of the control application. In this paper a reinforcement learning method is used to tune on line the conclusion part of fuzzy inference system rules. The fuzzy rules are tuned in order to maximize the return function . To illustrate its effectivness, the learning method is applied to the well known Cart-Pole balancing system problem. The results obtained show significant improvements of the speed of learning.|
|ISSN:||1112 - 3338|
|Appears in Collections:||CS N 01|
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