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Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming (2000) [1 citations — 0 self]

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by J. Eggermont , J.I. van Hemert

In Proceedings of the Twelveth Belgium /Netherlands Conference on Arti Intelligence (BNAIC'00

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@INPROCEEDINGS{Eggermont00stepwiseadaptation,
    author = {J. Eggermont and J.I. van Hemert},
    title = {Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming},
    booktitle = {In Proceedings of the Twelveth Belgium /Netherlands Conference on Arti Intelligence (BNAIC'00},
    year = {2000}
}

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Abstract:

In this paper we continue study on the Stepwise Adaptation of Weights (SAW) technique. Previous studies on constraint satisfaction and data classification have indicated that SAW is a promising technique to boost the performance of evolutionary algorithms. Here we use saw to boost performance of a genetic programming algorithm on simple symbolic regression problems. We measure the performance of a standard GP and two variants of SAW extensions on two different symbolic regression problems.

Citations

713	Genetic Programming – Koza - 1992
73	Coevolutionary computation – Paredis - 1995
34	Graph coloring with adaptive evolutionary algorithms – Eiben, Hauw, et al. - 1998
7	Adapting the function in GP for data mining – Eggermont, Eiben, et al. - 1999
4	SAW-ing EAs: adapting the function for solving constrained problems, chapter 26 – Eiben, Hemert - 1999
1	Genetic Programming II: Autmoatic Discovery of Reusable Programs – Koza - 1994