Intelligent exploration method for XCS

Exploration/Exploitation equilibrium is one of the most challenging issues in reinforcement learning area as well as learning classifier systems such as XCS. In this paper1 , an intelligent method is proposed to control 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. It Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning- Parameter Learning. General Terms Algorithms, Theory, Performance. Keywords Learning Classifier Systems, XCS, Exploration, Exploitation, Adaptive Exploration Rate.

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Ali Hamzeh, Adel Rahmani
• Keywords: Adaptive Exploration Rate, Classifier Systems, Exploration Rate, GECCO 2005