Skip to main content

Multi-agent Coordination in Planning

  • Conference paper
  • First Online:
PRICAI 2002: Trends in Artificial Intelligence (PRICAI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2417))

Included in the following conference series:

Abstract

We consider coordination problems where several agents, each assigned to some subtask of a complex task, solve their own sub-task by making minimal plans and want to find a common plan based on their individual plans. A task is conceived as a set of primitive tasks (operations), partially ordered by a set of precedence constraints. Operations are distributed among agents dependent on their capabilities and constitute the subtasks the agents have to solve. The precedence constraints between operations in subtasks are inherited from the overall precedence constraints occurring in the task. Since it is assumed that every agent is capable to find a suitable (minimal) plan for its own sub-task, the main problem for the agents to coordinate their plans in order to solve the complete task. First, we characterize situations in which an optimal coordinated plan can be constructed by simple plan coordination. Since, in general, obtaining optimal global plans is intractable, we therefore introduce two simple and efficient distributed approximation algorithms to achieve plan coordination.The first algorithm can be used as a d-approximation of a globally optimal plan for the agents, where d is the depth of the original task, i.e. the length of the longest chain in the set of precedence constraints constituting the task. This algorithm assumes almost no knowledge about the distribution of tasks over the agents. If such knowledge, however, is available, a second, more refined algorithm can be used, that is based on elaborate inter-agent negotiation and is able to achieve a better approximation ratio.

Jeroen Valk is supported by the TNO-TRAIL project IT-architecture and coordination in transport chains carried out within the research school for Transport, Infrastructure and Logistics (TRAIL).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R.J. Aumann. Survey of repeated games. In Essays in Game Theory and Mathematical Economics in Honor of Oskar Morgenstern, pages 11–42. Zurich, 1981.

    Google Scholar 

  2. R.J. Aumann and S. Hart, editors. Handbook of Game Theory with Economic Applications, volume 1. North-Holland, Amsterdam, 1992. Volume 2 appeared in 1994.

    Google Scholar 

  3. Tuomas Sandholm, Kate Larson, Martin Andersson, Onn Shehory, and Fernando Tohmé. Coalition structure generation with worst case guarantees. Artificial Intelligence, 111(1-2):209–238, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  4. Tuomas W. Sandholm and Victor R. Lesser. Coalitions among computationally bounded agents. Artificial Intelligence, 94:99–137, 1997.

    Article  MATH  MathSciNet  Google Scholar 

  5. Onn Shehory and Sarit Kraus. Methods for task allocation via agent coalition formation. Artificial Intelligence, 101(1-2):165–200, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  6. J.M. Valk, C. Witteveen, and J. Zutt. Approximation results for multi-agent planning systems. In Proceedings of the Pacific Rim International Workshop on Multi-Agents (PRIMA), 2001.

    Google Scholar 

  7. J. von Neumann and O. Morgenstern. Theory of Games and Economic Behavior. Princeton University Press, Princeton, 1944.

    MATH  Google Scholar 

  8. Gilad Zlotkin and Jeffrey S. Rosenschein. Mechanisms for coalition formation in task oriented domains. In Proceedings of the Twelfth National Conference on Artificial Intelligence, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Valk, J., Witteveen, C. (2002). Multi-agent Coordination in Planning. In: Ishizuka, M., Sattar, A. (eds) PRICAI 2002: Trends in Artificial Intelligence. PRICAI 2002. Lecture Notes in Computer Science(), vol 2417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45683-X_37

Download citation

  • DOI: https://doi.org/10.1007/3-540-45683-X_37

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44038-3

  • Online ISBN: 978-3-540-45683-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics