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On Two Types of GA-Learning

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 100))

Abstract

We distinguish two types of learning with a Genetic Algorithm. A population learning Genetic Algorithm (or pure GA), and an individual learning Genetic Algorithm (basically a GA combined with a Classifier System ). The difference between these two types of GA is often neglected, but we show that for a broad class of problems this difference is essential as it may lead to widely differing performances. The underlying cause for this is a so called spite effect.

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© 2002 Springer-Verlag Berlin Heidelberg

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Vriend, N.J. (2002). On Two Types of GA-Learning. In: Chen, SH. (eds) Evolutionary Computation in Economics and Finance. Studies in Fuzziness and Soft Computing, vol 100. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1784-3_13

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  • DOI: https://doi.org/10.1007/978-3-7908-1784-3_13

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2512-1

  • Online ISBN: 978-3-7908-1784-3

  • eBook Packages: Springer Book Archive

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