Intelligent exploration method for XCS

  • Authors:

  • Ali Hamzeh;Adel Rahmani

  • Affiliations:

  • Iran University of Science and Technology, CE School, IUST, Narmak, Tehran, Iran;Iran University of Science and Technology, CE School, IUST, Narmak, Tehran, Iran

  • Venue:
  • GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

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 paper, 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