Lawrence Bull Larry.Bull@uwe.ac.uk
School Director (Research & Enterprise) and Professor
Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks
Bull, Larry
Authors
Abstract
Abstract Michigan-style Classifier Systems use Genetic Algorithms to facilitate rule discovery. This paper presents a simple Markov model of the algorithm in such systems, with the aim of examining the effects of different types of interdependence between niches in multi-step tasks. Using the model it is shown that the existence of, what is here termed, partner rule variance can have significant and detrimental effects on the Genetic Algorithm's expected behaviour. Suggestions are made as to how to reduce these effects, making...
Citation
Bull, L. (2001). Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks. Lecture Notes in Artificial Intelligence, 1996, 29-36
Journal Article Type | Article |
---|---|
Publication Date | Jan 1, 2001 |
Journal | Lecture Notes in Computer Science |
Print ISSN | 0302-9743 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 1996 |
Pages | 29-36 |
Keywords | Markov, models, genetic algorithm, classifier systems, multi step tasks |
Public URL | https://uwe-repository.worktribe.com/output/1090721 |
Publisher URL | http://www.springerlink.com |
You might also like
Towards the evolution of vertical-axis wind turbines using supershapes
(2014)
Journal Article
Evolving unipolar memristor spiking neural networks
(2015)
Journal Article
Evolving functional and structural dynamism in coupled boolean networks
(2014)
Journal Article
A brief history of learning classifier systems: from CS-1 to XCS and its variants
(2015)
Journal Article
Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system
(2013)
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