Controlling a simulated Khepera with an XCS classifier system with memory.

Webb, Andrew; Hart, Emma; Ross, Peter; Lawson, Alistair

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.

Citation

Webb, A., Hart, E., Ross, P., & Lawson, A. (2003). Controlling a simulated Khepera with an XCS classifier system with memory.

• Conference Name: 7th European Conference on Artificial Life, ECAL 2003: Advances in Artificial Life
• Start Date: Sep 14, 2003
• End Date: Sep 17, 2003
• Publication Date: Sep 14, 2003
• Deposit Date: Jul 22, 2008
• Electronic ISSN: 1611-3349
• Peer Reviewed: Peer Reviewed
• Pages: 885-892
• ISBN: 9783540200574
• Keywords: Robot sensors; Internal memory states; Khepera environments
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/1759
• Publisher URL: http://www.springerlink.com/content/4khd5dfq1kn14dhu/