article · 2008
BCS: a Bayesian Learning Classifier System
Hai H. Dam, Hussien A. Abbass, Chris Lokan, Hai H. Dam, Hussien A. Abbass, Chris Lokan
Cited by 0Abstract and details only
Abstract
Genetics-based machine learning systems have been applied in many areas. Among them, XCS is one of the most advanced systems for reinforcement learning. UCS is a specialized case of XCS for data mining and supervised learning. In this paper we show that both XCS and UCS are quite sensitive to noise, and we propose an alternative system with Bayesian update called BCS. An experiment shows that BCS outperforms both XCS and UCS in a multiplexer problem and is quite robust to noise. I.
Cite this paper
Dam, H. H., Abbass, H. A., Lokan, C., Dam, H. H., Abbass, H. A., & Lokan, C. (2008). BCS: a Bayesian Learning Classifier System.
Dam, Hai H., et al. “BCS: a Bayesian Learning Classifier System.” 2008.
Dam, Hai H., Hussien A. Abbass, Chris Lokan, Hai H. Dam, Hussien A. Abbass, and Chris Lokan. 2008. “BCS: a Bayesian Learning Classifier System.”
Dam, H.H. et al. (2008) ‘BCS: a Bayesian Learning Classifier System’.
@article{dam2008bayesian,
title = {{BCS: a Bayesian Learning Classifier System}},
author = {Dam, Hai H. and Abbass, Hussien A. and Lokan, Chris and Dam, Hai H. and Abbass, Hussien A. and Lokan, Chris},
year = {2008}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.