A controlled genetic programming approach for the deceptive domain.
Traditional genetic programming (GP) randomly combines subtrees by applying crossover. There is a growing interest in methods that can control such recombination operations in order to achieve faster convergence. In this paper, a new approach is presented for guiding the recombination process for genetic programming. The method is based on extracting the global information of the promising solutions that appear during the genetic search. The aim is to use this information to control the crossover operation afterwards. A separate control module is used to process the collected information. This module guides the search process by sending feedback to the genetic engine about the consequences of possible recombination alternatives.
Department of Computer Engineering, Middle East Technical University, 06531 Ankara, Turkey. korkmaz@ceng.metu.edu.tr
Emin Erkan
EE
Korkmaz
Göktürk
G
Uçoluk
D000465:Algorithms; D001185:Artificial Intelligence; D005075:Biological Evolution; D003198:Computer Simulation; D003661:Decision Support Techniques; D008957:Models, Genetic; D008962:Models, Theoretical; D011382:Programming, Linear