Temporal Enhancements of an HTN Planner

  • Luis Castillo
  • Juan Fdez-Olivares
  • Óscar García-Pérez
  • Francisco Palao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4177)


This paper presents some enhancements in the temporal reasoning of a Hierarchical Task Network (HTN) planner, named SIADEX, that, up to authors knowledge, no other HTN planner has. These new features include a sound partial order metric structure, deadlines, temporal landmarking or synchronization capabilities built on top of a Simple Temporal Network [3].


Inference Rule Causal Structure Temporal Constraint High Level Task Abductive Inference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Allen, J.F.: Maintaining knowledge about temporal intervals. Comm. ACM 26(1), 832–843 (1983)MATHCrossRefGoogle Scholar
  2. 2.
    de la Asunción, M., Castillo, L., Fdez-Olivares, J., García-Pérez, O., González, A., Palao, F.: Siadex: an interactive artificial intelligence planner for decision support and training in forest fire fighting. Artificial Intelligence Communications 18(4) (2005)Google Scholar
  3. 3.
    Dechter, R.: Constraint processing. Morgan Kaufmann, San Francisco (2003)Google Scholar
  4. 4.
    Edelkamp, S., Hoffmann, J.: The language for the 2004 international planning competition (2004),
  5. 5.
    Fox, M., Long, D.: Domains of the 3rd. international planning competition. In: Artificial Intelligence Planning Systems, AIPS 2002 (2002)Google Scholar
  6. 6.
    Gil, Y., Blythe, J.: PLANET: A shareable and reusable ontology for representing plans. In: AAAI 2000 workshop on representational issues for real-world planning systems (2000)Google Scholar
  7. 7.
    McIlraith, S.A.: Integrating actions and state constraints: A closed-form solution to the ramification problem (sometimes). Artificial Intelligence Journal, 87–121 (2000)Google Scholar
  8. 8.
    Nau, D., Au, T.C., Ilghami, O., Kuter, U., Murdock, J.W., Wu, D., Yaman, F.: SHOP2: An HTN Planning System. Journal of Artificial Intelligence Research 20, 379–404 (2003)MATHGoogle Scholar
  9. 9.
    Wilkins, D.E.: Practical planning: Extending the classical AI planning paradigm. Morgan Kaufmann, San Francisco (1988)Google Scholar
  10. 10.
    Wilkins, D.E., des Jardins, M.: A call for knowledge-based planning. AI Magazine 22(1), 99–115 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Luis Castillo
    • 1
  • Juan Fdez-Olivares
    • 1
  • Óscar García-Pérez
    • 1
  • Francisco Palao
    • 1
  1. 1.Dpto. Ciencias de la Computación e I.A.University of Granada 

Personalised recommendations