Journal of Scheduling

, Volume 13, Issue 4, pp 347–362

Automatic generation of temporal planning domains for e-learning problems

  • Luis Castillo
  • Lluvia Morales
  • Arturo González-Ferrer
  • Juan Fdez-Olivares
  • Daniel Borrajo
  • Eva Onaindía
Article

DOI: 10.1007/s10951-009-0140-x

Cite this article as:
Castillo, L., Morales, L., González-Ferrer, A. et al. J Sched (2010) 13: 347. doi:10.1007/s10951-009-0140-x

Abstract

AI Planning & Scheduling techniques are being widely used to adapt learning paths to the special features and needs of students both in distance learning and lifelong learning environments. However, instructors strongly rely on Planning & Scheduling experts to encode and review the domains for the planner/scheduler to work. This paper presents an approach to automatically extract a fully operational HTN planning domain and problem from a learning objects repository without requiring the intervention of any planning expert, and thus enabling an easier adoption of this technology in practice. The results of a real experiment with a small group of students within an e-Learning private company in Spain are also shown.

Hierarchical task network planning Knowledge engineering for planning and scheduling Applications to e-learning 

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Luis Castillo
    • 1
  • Lluvia Morales
    • 1
  • Arturo González-Ferrer
    • 2
  • Juan Fdez-Olivares
    • 1
  • Daniel Borrajo
    • 3
  • Eva Onaindía
    • 4
  1. 1.Departamento de Ciencias de la Computación e I.A., ETSI Informática y TelecomunicacionesUniversidad de GranadaGranadaSpain
  2. 2.Center for Virtual Teaching, E-Learning CenterUniversity of GranadaGranadaSpain
  3. 3.Departamento de InformáticaUniversidad Carlos III de MadridLeganésSpain
  4. 4.Departamento de Sistemas Informáticos y ComputaciónUniversidad Politécnica de ValenciaValenciaSpain