A PDDL Based Tool for Automatic Web Service Composition

  • Joachim Peer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3208)


One of the motivations for research in semantic web services is to automatically compose web service operations to solve given problems. The idea of using AI planning software to this end has been suggested by several papers. The present paper follows this approach but argues that the diversity of the web service domains is best addressed by a flexible combination of complementary reasoning techniques and planning systems. We present a tool that transforms web service composition problems into AI planning problems and delegates them to the planners most suitable for the particular planning task. The tool uses PDDL, a language supported by a wide range of planning engines, as a transfer format. The present paper describes the tool and its strategies to cope with the problems of incomplete information, various types of web service indeterminism, stateful services and structurally rich goal specifications.


Service Execution Closed World Assumption Service Annotation Complex Goal Goal Description 
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.
    W3C: Web Service Description Language (WSDL) version 1.2 (2002)Google Scholar
  2. 2.
    Srivastava, B., Koehler, J.: Web Service Composition - Current Solutions and Open Problems. In: Proceedings of ICAPS 2003 Workshop on Planning for Web Services, Trento, Italy (June 2003)Google Scholar
  3. 3.
    McIlraith, S., Son, T.: Adapting Golog for composition of semantic web services. In: Proceedings of the Eighth International Conference on Knowledge Representation and Reasoning (KR 2002), Toulouse, France (April 2002) Google Scholar
  4. 4.
    Hendler, J., Wu, D., Sirin, E., Nau, D., Parsia, B.: Automatic web services composition using SHOP2. In: Proceedings of The Second International Semantic Web Conference, ISWC (2003)Google Scholar
  5. 5.
    Hoffmann, J., Nebel, B.: The FF planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence Research, JAIR (2001)Google Scholar
  6. 6.
    Younes, H.L.S., Simmons, R.G.: VHPOP: Versatile Heuristic Partial Order Planner. Journal of Artificial Intelligence Research (2003) Google Scholar
  7. 7.
    Gerevini, A., Saetti, A., Serina, I.: Planning through stochastic local search and temporal action graphs. Journal of Artificial Intelligence Research (JAIR) (to appear)Google Scholar
  8. 8.
    Ghallab, M., Howe, A., Knoblock, C., McDermott, D., Ram, A., Veloso, M., Weld, D., Wilkins, D.: PDDL—the planning domain definition language. In: AIPS 1998 Planning Committee (1998) Google Scholar
  9. 9.
    Golden, K.: Planning and knowledge representation for softbots (1997) Google Scholar
  10. 10.
    McDermott, D.: Estimated-regression planning for interactions with web services. In: Proc. of the AI Planning Systems Conference 2002 (2002)Google Scholar
  11. 11.
    Bertoli, P., Cimatti, A., Lago, U.D., Pistore, M.: Extending PDDL to nondeterminism, limited sensing and iterative conditional plans. In: ICAPS 2003, Workshop on PDDL (2003)Google Scholar
  12. 12.
    Sun Microsystems: JavaServer pages standard tag library (2003) Google Scholar
  13. 13.
    Carman, M., Serafini, L.: Planning for web services the hard way. In: Symposium on Applications and the Internet Workshops (SAINT 2003 Workshops), Orlando, Florida (2003)Google Scholar
  14. 14.
    Koenig, S.: Agent-centered search. Artificial Intelligence Magazine (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Joachim Peer
    • 1
  1. 1.Institute for Media and Communications ManagementUniversity of St. GallenSwitzerland

Personalised recommendations