An accuracy-based neural classifier system

Bull, Larry; O�Hara, Toby

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 ...

• 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• Peer Reviewed: Not Peer Reviewed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/