Lawrence Bull Larry.Bull@uwe.ac.uk
School Director (Research & Enterprise) and Professor
An accuracy-based neural classifier system
Bull, Larry; O�Hara, Toby
Authors
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Peer Reviewed | Not Peer Reviewed |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/ |
You might also like
A generalised dropout mechanism for distributed systems
(2022)
Journal Article
Evolving Boolean regulatory networks with variable gene expression times
(2021)
Book Chapter
On coevolution: Asymmetry in the NKCS model
(2021)
Journal Article
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search