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Arithmetic dynamical genetic programming in the XCSF learning classifier system

Preen, Richard; Bull, Larry

Authors

Lawrence Bull Larry.Bull@uwe.ac.uk
School Director (Research & Enterprise) and Professor



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 ...

Citation

Preen, R., & Bull, L. (2011, June). Arithmetic dynamical genetic programming in the XCSF learning classifier system. Paper presented at IEEE Congress on Evolutionary Computation (CEC), 2011, New Orleans, US

Presentation Conference Type Conference Paper (unpublished)
Conference Name IEEE Congress on Evolutionary Computation (CEC), 2011
Conference Location New Orleans, US
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