Title :
Inductive Logic Programming through Estimation of Distribution Algorithm
Author :
Pitangui, Cristiano Grijó ; Zaverucha, Gerson
Author_Institution :
COPPE, Fed. Univ. of Rio de Janeiro, Rio de Janeiro, Brazil
Abstract :
Genetic Algorithms (GAs) are known for their capacity to explore large search spaces and due to this ability, they were to some extent applied to Inductive Logic Programming (ILP) problem. Although Estimation of Distribution Algorithms (EDAs) perform better in most problems when compared to standard GAs, this kind of algorithm have not been applied to ILP. This work presents an ILP system based on EDA. Preliminary results show that the proposed system is superior when compared to a "standard" GA and it is very competitive when compared to the state of the art ILP system Aleph.
Keywords :
genetic algorithms; inductive logic programming; Aleph; EDA; GA; ILP system; artificial intelligence; estimation of distribution algorithm; genetic algorithms; inductive logic programming problem; Bayesian methods; Genetic algorithms; Lattices; Logic programming; Probabilistic logic; Search problems; Space exploration; Estimation of Distribution Algorithms; Inductive Logic Programming; Probabilistic Models;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949597
