Controlling a Simulated Khepera with an XCS Classifier System with Memory

  • Andrew Webb
  • Emma Hart
  • Peter Ross
  • Alistair Lawson
Conference paper

DOI: 10.1007/978-3-540-39432-7_95

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2801)
Cite this paper as:
Webb A., Hart E., Ross P., Lawson A. (2003) Controlling a Simulated Khepera with an XCS Classifier System with Memory. In: Banzhaf W., Ziegler J., Christaller T., Dittrich P., Kim J.T. (eds) Advances in Artificial Life. ECAL 2003. Lecture Notes in Computer Science, vol 2801. Springer, Berlin, Heidelberg

Abstract

Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of action. One technique for addressing this problem is to use additional internal states within a reinforcement learning system, in particular a learning classifier system. Previous research has shown that adding internal memory states can allow an animat within a cellular world to successfully navigate complex mazes. However, the technique has not previously been applied to robotic environments in which sensory data is noisy and somewhat unpredictable. We present results of using XCS with additional internal memory in the simulated Khepera environment, and show that control rules can be evolved to allow the robot to navigate a variety of problems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Andrew Webb
    • 1
  • Emma Hart
    • 1
  • Peter Ross
    • 1
  • Alistair Lawson
    • 1
  1. 1.Napier UniversityEdinburghScotland, UK

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