Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems

Abstract. In this paper we continue our study on adaptive genetic programming. We use Stepwise Adaptation of Weights (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 from literature. Also, we propose a model for randomly generating polynomials which we then use to further test all three gp variants.

• Type: Conference
• Year: 2001
• Where: EUROGP
• Authors: Jeroen Eggermont, Jano I. van Hemert
• Keywords: EUROGP 2001, Genetic Programming, Optimization, Simple Symbolic Regression, Symbolic Regression Problems