Arithmetic dynamical genetic programming in the XCSF learning classifier system

Preen, Richard; Bull, Larry

Abstract

This paper presents results from an investigation into using a continuous-valued dynamical system representation within the XCSF Learning Classifier System. In particular,
dynamical arithmetic genetic networks are used to represent the traditional condition-action production system rules. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF. The results presented herein show that the collective emergent behaviour of the evolved systems exhibits competitive ...

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: IEEE Congress on Evolutionary Computation (CEC), 2011
• Start Date: Jun 5, 2011
• End Date: Jun 8, 2011
• Publication Date: Jan 1, 2011
• Peer Reviewed: Peer Reviewed
• Pages: 1428-1435
• Keywords: genetic algorithms, learning systems, pattern classification, polynominal approximation, regression analysis
• Public URL: https://uwe-repository.worktribe.com/output/971078
• Publisher URL: http://dx.doi.org/10.1109/CEC.2011.5949783
• Additional Information: Title of Conference or Conference Proceedings : IEEE Congress on Evolutionary Computation (CEC), 2011