• DocumentCode
    2963478
  • Title

    Creating adaptive learning paths using Ant Colony Optimization and Bayesian Networks

  • Author

    Márquez, José Manuel ; Ortega, Juan Antonio ; González-Abril, Luis ; Velasco, Francisco

  • Author_Institution
    R&D Dept., Telvent, Sevilla
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    3834
  • Lastpage
    3839
  • Abstract
    This paper presents a new way to combine two different approaches of artificial intelligence looking for the best path in a graph, ant colony optimization and Bayesian networks. The main objective is to develop a learning management system which will have the capability of adapting the learning path to the learnerpsilas needs in execution time, taking into account the pedagogical weight of each learning unit and the systempsilas social behavior.
  • Keywords
    belief networks; learning (artificial intelligence); optimisation; Bayesian networks; adaptive learning paths; ant colony optimization; artificial intelligence; learning management system; Ant colony optimization; Bayesian methods; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4634349
  • Filename
    4634349