Keywords : Crossover

Design and Implementation of ILP Based Selection Algorithm for Genetic Programming system (ILPSAGP)

Rabah Nory Farhan

Journal of Al-Qadisiyah for Computer Science and Mathematics, 2010, Volume 2, Issue 1, Pages 1-10

Genetic Programming is one of the evolutionary algorithms developed to solve wide area of industrial and scientific problems. Rather than dealing with population of string like Genetic Algorithm, Genetic Programming composes the first population from programs tree derived from the function set of the problem. In this paper, we extend the selection algorithm of the GP by using the Learning Classifier System, which build and derive the Hypothesis set from the population. The selection algorithm redesigned to enforce the selection been added from the Hypothesis domain. The proposed system called ILPSAGP was built using 2008 and tested with traditional problem like Line Regression problem. The obtained results shows more accurate result than traditional Genetic Programming.