Newboole: A Fast GBML System
Abstract
Genetics based machine learning systems are considered by a majority of machine learners as slow rate learning systems. In this paper, we propose an improvement of Wilson's classifier system BOOLE that shows how Genetics based machine learning systems learning rates can be greatly improved. This modification consists in a change of the reinforcement component. We then compare the respective performances of this modified BOOLE, called NEWBOOLE, and a neural net using back propagation on a difficult boolean learning task, the multiplexer function. The results of this comparison show that NEWBOOLE obtains significantly faster learning rates.
Cite
Text
Bonelli et al. "Newboole: A Fast GBML System." International Conference on Machine Learning, 1990. doi:10.1016/B978-1-55860-141-3.50022-5Markdown
[Bonelli et al. "Newboole: A Fast GBML System." International Conference on Machine Learning, 1990.](https://mlanthology.org/icml/1990/bonelli1990icml-newboole/) doi:10.1016/B978-1-55860-141-3.50022-5BibTeX
@inproceedings{bonelli1990icml-newboole,
title = {{Newboole: A Fast GBML System}},
author = {Bonelli, Pierre and Parodi, Alexandre and Sen, Sandip and Wilson, Stewart W.},
booktitle = {International Conference on Machine Learning},
year = {1990},
pages = {153-159},
doi = {10.1016/B978-1-55860-141-3.50022-5},
url = {https://mlanthology.org/icml/1990/bonelli1990icml-newboole/}
}