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.
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Hamzeh, A., Rahmani, A. (2007). A Fuzzy System to Control Exploration Rate in XCS. In: Kovacs, T., Llorà , X., Takadama, K., Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS IWLCS IWLCS 2003 2004 2005. Lecture Notes in Computer Science(), vol 4399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71231-2_9
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DOI: https://doi.org/10.1007/978-3-540-71231-2_9
Publisher Name: Springer, Berlin, Heidelberg
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