Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming
Jeroen Eggermont, Jano I. Van Hemert · 2001
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.