English

On the Effectiveness of Genetic Operations in Symbolic Regression

Machine Learning 2021-08-25 v1 Neural and Evolutionary Computing

Abstract

This paper describes a methodology for analyzing the evolutionary dynamics of genetic programming (GP) using genealogical information, diversity measures and information about the fitness variation from parent to offspring. We introduce a new subtree tracing approach for identifying the origins of genes in the structure of individuals, and we show that only a small fraction of ancestor individuals are responsible for the evolvement of the best solutions in the population.

Keywords

Cite

@article{arxiv.2108.10661,
  title  = {On the Effectiveness of Genetic Operations in Symbolic Regression},
  author = {Bogdan Burlacu and Michael Affenzeller and Michael Kommenda},
  journal= {arXiv preprint arXiv:2108.10661},
  year   = {2021}
}

Comments

International Conference on Computer Aided Systems Theory, Eurocast 2015, pp 367-374