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An accuracy-based neural classifier system

Bull, Larry; O�Hara, Toby

Authors

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

Toby O�Hara



Abstract

Learning Classifier Systems have traditionally used a binary representation, with wildcards added to facilitate generalization. As they are applied to more complex domains the simple representation can become limiting. In this paper we present results from the use of a neural network-based representation scheme within the accuracy-based XCS. Here each rule's condition and action are represented by a small neural network, evolved through the actions of the genetic algorithm. After describing the changes required to the standard ...

Citation

Bull, L., & O’Hara, T. (2001). An accuracy-based neural classifier system

Report Type Technical Report
Publication Date Jan 1, 2001
Peer Reviewed Not Peer Reviewed
Keywords neural classifier system, computing
Public URL https://uwe-repository.worktribe.com/output/1090747
Publisher URL http://www.cems.uwe.ac.uk/lcsg/