Abstract
Exploration/Exploitation dilemma is one of the most challenging issues in reinforcement learning area as well as learning classifier systems such as XCS. In this paper, an intelligent method is proposed to control the exploration rate in XCS to improve its long-term performance. This method is called Intelligent Exploration Method (IEM) and is applied to some benchmark problems to show advantages of adaptive exploration rate for XCS. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Hamzeh, A., & Rahmani, A. (2007). A fuzzy system to control exploration rate in XCS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4399 LNAI, pp. 115–127). Springer Verlag. https://doi.org/10.1007/978-3-540-71231-2_9
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