On the influence of different number generators on results of the symbolic regression

Abstract

This paper deals with mutual comparison of different pseudorandom number generators and its impact on the performance of selected algorithms of the symbolic regression. In this paper we discuss the use of genetic programming (GP) with use of chaotic systems as well as its main attributes and universal features. It is also explained why deterministic chaos is used and compared here with standard pseudorandom number generators. Based on the characterization of deterministic chaos, universal features of that kind of behavior are explained. In the second part of the paper we discuss selected examples of GP powered by deterministic chaos and classical pseudorandom number generators and its results.