• DocumentCode
    2214682
  • 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
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    54
  • Lastpage
    61
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949597
  • Filename
    5949597