Created by W.Langdon from gp-bibliography.bib Revision:1.8028
In this paper we apply crossover bias to several problems. In most cases we found that crossover bias either improved performance or had no impact. We also found that the effectiveness of crossover bias is dependent on the problem, and significantly dependent on other parameter choices.
While this work focuses specifically on sub-tree crossover in tree-based GP, artificial and biological evolutionary systems often have substantial asymmetries, many of which remain understudied. This work suggests that there is value in further exploration of the impacts of these asymmetries.",
Genetic Programming entries for Nicholas Freitag McPhee M Kirbie Dramdahl David Donatucci