Wise Breeding GA via Machine Learning Techniques for Function Optimization (2003)
| Venue: | Lecture Notes in Computer Science, 2723:1172 |
| Citations: | 5 - 0 self |
BibTeX
@INPROCEEDINGS{Llora03wisebreeding,
author = {Xavier Llora and Xavier Llora and David E. Goldberg and David E. Goldberg},
title = {Wise Breeding GA via Machine Learning Techniques for Function Optimization},
booktitle = {Lecture Notes in Computer Science, 2723:1172},
year = {2003},
pages = {1172--1183},
publisher = {Springer}
}
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Abstract
This paper explores how inductive machine learning can guide the breeding process of evolutionary algorithms for black-box function optimization. In particular, decision trees are used to identify the underlying characteristics of good and bad individuals, using the mined knowledge for wise breeding purposes. Inductive learning is complemented with statistical learning in order to define the breeding process. The proposed evolutionary process optimizes the target function dually, maximizing and minimizing it at the same time. The paper also summarize some tuning and population sizing issues, as well as some preliminary results obtained using the proposed algorithm.
