Learning with Genetic Algorithms: An Overview (1988)
| Venue: | MACHINE LEARNING |
| Citations: | 83 - 5 self |
BibTeX
@ARTICLE{Jong88learningwith,
author = {Kenneth De Jong},
title = { Learning with Genetic Algorithms: An Overview},
journal = {MACHINE LEARNING},
year = {1988},
volume = {3},
pages = {123--138}
}
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Abstract
Genetic algorithms represent a class of adaptive search techniques that have been intensively studied in recent years, Much of the interest in genetic algorithms is due to the fact that they provide a set of efficient domain-independent search heuristics which are a significant improvement over traditional "weak methods" without the need for incorporating highly domain-specific knowledge. There is now considerable evidence that genetic algorithms are useful for global function optimization and NP-hurd problems. Recently, there has been a good deal of interest in using genetic algorithms for machine learning problems. This paper provides a brief overview of how one might use genetic algorithms as a key element in learning systems.
