Hybrid Multi-agent Planning

  • Mohamed Elkawkagy
  • Susanne Biundo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6973)


Although several approaches have been constructed for multi-agent planning, solving large planning problems is still quite difficult. In this paper, we present a new approach that integrates landmark preprocessing technique in the context of hierarchical planning with multi-agent planning. Our approach uses Dependent and Independent clustering techniques to break up the planning problem into smaller clusters. These clusters are solved individually according to landmark information, then the obtained individual plans are merged according to the notion of fragments to generate a final solution plan. In hierarchical planning, landmarks are those tasks that occur in the decomposition refinements on every plan development path. Hierarchical landmark technique shows how a preprocessing step that extracts landmarks from a hierarchical planning domain and problem description can be used to prune the search space that is to be explored before actual search is performed. The methodologies in this paper have been implemented successfully, and we will present some experimental results that give evidence for the considerable performance increase gained through our system.


Planning Problem Solution Plan Initial Plan Local Landmark Individual Plan 
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.


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  1. 1.
    Biundo, S., Schattenberg, B.: From abstract crisis to concrete relief (a preliminary report on combining state abstraction and HTN planning). In: Proc. of ECP, pp. 157–168 (2001)Google Scholar
  2. 2.
    Bradley, J., Edmund, H.: Theory for coordinating concurrent hierarchical planning agents using summary information. In: Proc. of AAAI, pp. 495–502 (1999)Google Scholar
  3. 3.
    Corkill, D.: Hierarchical planning in a distributed environment. In: Proc. of IJCAI, pp. 168–175 (1979)Google Scholar
  4. 4.
    desJardins, M., Wolverton, M.: Coordinating a distributed planning system. Journal of AI Magazine 20(4), 4553 (1999)Google Scholar
  5. 5.
    Elkawkagy, M., Schattenberg, B., Biundo, S.: Landmarks in hierarchical planning. In: Proc. of ECAI, pp. 229–234 (2010)Google Scholar
  6. 6.
    Elkawkagy, M., Bercher, P., Schattenberg, B., Biundo, S.: Exploiting landmarks for hybrid planning. In: 25th PuK Workshop Planen, Scheduling und Konfigurieren, Entwerfen (2010)Google Scholar
  7. 7.
    Erol, K., Hendler, J., Nau, D.: UMCP: A sound and complete procedure for hierarchical task-network planning. In: Proc. of AIPS, pp. 249–254 (1994)Google Scholar
  8. 8.
    Hayashi, H.: Stratified multi-agent HTN planning in dynamic environments. In: Nguyen, N.T., Grzech, A., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2007. LNCS (LNAI), vol. 4496, pp. 189–198. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Jeffrey, S., Edmund, D.: An efficient algorithm for multiagent plan coordination. In: Proc. of the AAMAS, pp. 828–835 (2005)Google Scholar
  10. 10.
    Mors, A.W., Valk, J.M., Witteveen, C.: Task coordination and decomposition in multi-actor planning systems. In: Proc. of the Workshop on Software-Agents in Information Systems and Industrial Applications (SAISIA), pp. 83–94 (2006)Google Scholar
  11. 11.
    Schattenberg, B.: Hybrid planning and scheduling. PhD thesis, The University of Ulm, Institute of Artificial Intelligence (2009)Google Scholar
  12. 12.
    Tonino, J., Bos, A., de Weerdt, M.M., Witteveen, C.: Plan coordination by revision in collective agent-based systems. Journal of Artificial Intelligence 142(2), 121–145 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Weerdt, M., Witteveen, C.: A resource logic for multi-agent plan merging. In: Proc. of the 20th Workshop of the UK planning and Scheduling, pp. 244–256 (2003)Google Scholar
  14. 14.
    Wilkins, D.E., Mayers, K.L.: A multi-agent planning architecture. In: Proc. of AIPS 1998, pp. 154–162 (1998)Google Scholar
  15. 15.
    Yang, Q., Nau, D.S., Hendler, J.: Merging separately generated plans with restricted interactions. Journal of Computational Intelligence 8(4), 648–676 (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mohamed Elkawkagy
    • 1
  • Susanne Biundo
    • 1
  1. 1.Dept. of Artificial IntelligenceUlm UniversityUlmGermany

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