Design and Implementation of ILP Based Selection Algorithm for Genetic Programming system (ILPSAGP)
Keywords:
Genetic Programming, Inductive Logic Programming, Selection Algorithms, Crossover, Mutation, S-Expression.Abstract
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 C#.net 2008 and
tested with traditional problem like Line Regression problem. The obtained results
shows more accurate result than traditional Genetic Programming.
