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Paper ID: 2713

Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems
Eggermont,J. van Hemert,J.I. ,

Appeared in: Springer Lecture Notes on Computer Science,
Page Numbers:23--35
Publisher: Springer-Verlag, Berlin
Year: 2001
ISBN/ISSN: 9-783540-418993
Contributing Organisation(s):
Field of Science: e-Science

URL:

Abstract: In this paper we continue our study on adaptive genetic pro-gramming. We use Stepwise Adaptation of Weights 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 prob-lems from literature. Also, we propose a model for randomly generating polynomials which we then use to further test all three GP variants.

Keywords: data, mining,


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