Abstract
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
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)
Bradley, J., Edmund, H.: Theory for coordinating concurrent hierarchical planning agents using summary information. In: Proc. of AAAI, pp. 495–502 (1999)
Corkill, D.: Hierarchical planning in a distributed environment. In: Proc. of IJCAI, pp. 168–175 (1979)
desJardins, M., Wolverton, M.: Coordinating a distributed planning system. Journal of AI Magazine 20(4), 4553 (1999)
Elkawkagy, M., Schattenberg, B., Biundo, S.: Landmarks in hierarchical planning. In: Proc. of ECAI, pp. 229–234 (2010)
Elkawkagy, M., Bercher, P., Schattenberg, B., Biundo, S.: Exploiting landmarks for hybrid planning. In: 25th PuK Workshop Planen, Scheduling und Konfigurieren, Entwerfen (2010)
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)
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)
Jeffrey, S., Edmund, D.: An efficient algorithm for multiagent plan coordination. In: Proc. of the AAMAS, pp. 828–835 (2005)
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)
Schattenberg, B.: Hybrid planning and scheduling. PhD thesis, The University of Ulm, Institute of Artificial Intelligence (2009)
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)
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)
Wilkins, D.E., Mayers, K.L.: A multi-agent planning architecture. In: Proc. of AIPS 1998, pp. 154–162 (1998)
Yang, Q., Nau, D.S., Hendler, J.: Merging separately generated plans with restricted interactions. Journal of Computational Intelligence 8(4), 648–676 (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Elkawkagy, M., Biundo, S. (2011). Hybrid Multi-agent Planning. In: Klügl, F., Ossowski, S. (eds) Multiagent System Technologies. MATES 2011. Lecture Notes in Computer Science(), vol 6973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24603-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-24603-6_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24602-9
Online ISBN: 978-3-642-24603-6
eBook Packages: Computer ScienceComputer Science (R0)