Plan-Coordination Mechanisms and the Price of Autonomy

  • J. Renze Steenhuisen
  • Cees Witteveen
  • Yingqian Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5056)


Task-based planning problems for multi-agent systems require multiple agents to find a joint plan for a constrained set of tasks. Typically, each agent receives a subset of tasks to complete. Due to task interdependencies, such task allocations induce interdependencies between agents as well. These interdependencies will prevent the agents from making a plan for their subset of tasks independently from each other, since the combination of such autonomously constructed plans will most probably result in conflicting plans. Therefore, a plan-coordination mechanism is needed to guarantee a conflict-free globally feasible plan.

In this paper, we first present a brief overview of the main results achieved on plan coordination for autonomous planning agents, distinguishing between problems associated with deciding whether a coordination mechanism is necessary, designing an arbitrary coordination mechanism, and designing an optimal (minimal) coordination mechanism. After finding out that designing an optimal coordination mechanism is difficult, we concentrate on an algorithm that is able to find a (non-trivial) coordination mechanism that is not always minimal. We then discuss some subclasses of plan-coordination instances where this algorithm performs very badly, but also some class of instances where a nearly optimal coordination mechanism is returned.

Hereafter, we discuss the price of autonomy as a measure to determine the loss of (global) performance of a system due to the use of a coordination mechanism, and we offer a case study on multi-modal transportation where a coordination mechanism can be designed that offers minimal restrictions and guarantee nearly optimal performance. We will also place the use of these coordination mechanisms in a more general perspective, claiming that they can be used to reuse existing (single) agent software in a complex multi-agent environment.

Finally, we briefly discuss some recent extensions of our coordination framework dealing with temporal planning aspects.


Complex tasks planning coordination autonomy multi-agent systems 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Shehory, O., Kraus, S.: Methods for task allocation via agent coalition formation. Artificial Intelligence 101, 165–200 (1998)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Zlot, R.M., Stentz, A.: Market-based multirobot coordination for complex tasks. In: International Journal of Robotics Research, Special Issue on the 4th Int. Conf. on Field and Service Robotics, vol. 25, pp. 73–101 (2006)Google Scholar
  3. 3.
    Christodoulou, G., Koutsoupias, E., Nanavati, A.: Coordination mechanisms. In: Díaz, J., Karhumäki, J., Lepistö, A., Sannella, D. (eds.) ICALP 2004. LNCS, vol. 3142, pp. 345–357. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Smith, S.F., Gallagher, A., Zimmerman, T., Barbulescu, L., Rubinstein, Z.: Distributed management of flexible times schedules. In: Proc. of the 6th Int. Joint Conf. on Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 472–479 (2007)Google Scholar
  5. 5.
    Decker, K.S., Lesser, V.R.: Designing a family of coordination algorithms. In: Proc. of the 1st Int. Conf. on Multi-Agent Systems (ICMAS), San Francisco, CA, USA. AAAI Press, MIT Press (1995)Google Scholar
  6. 6.
    Cox, J.S., Durfee, E.H.: Efficient mechanisms for multiagent plan merging. In: Proc. of the 3rd Int. Joint Conf. on Autonomous Agents and Multi-Agent Systems (AAMAS), Washington, DC, USA, aug 2004, vol. 3, pp. 1342–1343. IEEE Computer Society, Los Alamitos (2004)Google Scholar
  7. 7.
    Sandhlom, T.W., Lesser, V.R.: Coalitions among computationally bounded agents. Artificial Intelligence 94, 99–137 (1997)MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    Walsh, W.E., Wellman, M.P.: A market protocol for decentralized task allocation and scheduling with hierarchical dependencies. In: Proc. of the 3rd Int. Conf. on Multi-Agent Systems (ICMAS), pp. 325–332. IEEE Computer Society Press, Los Alamitos (1999)Google Scholar
  9. 9.
    Gerkey, B.P., Matarić, M.J.: A formal analysis and taxonomy of task allocation in multi-robot systems. Journal of Robotics Research 23, 939–954 (2004)CrossRefGoogle Scholar
  10. 10.
    Dias, M.B., Stentz, A.: Traderbots: A market-based approach for resource, role, and task allocation in multirobot coordination. Technical Report CMU-RI-TR-03-19, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA (2003)Google Scholar
  11. 11.
    Buzing, P.C., ter Mors, A.W., Valk, J.M., Witteveen, C.: Coordinating self-interested planning agents. Autonomous Agents and Multi-Agent Systems 12, 199–218 (2006)CrossRefGoogle Scholar
  12. 12.
    Steenhuisen, J.R., Witteveen, C., ter Mors, A.W., Valk, J.M.: Framework and complexity results for coordinating non-cooperative planning agents. In: Fischer, K., Timm, I.J., André, E., Zhong, N. (eds.) MATES 2006. LNCS (LNAI), vol. 4196, pp. 98–109. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman and Company, San Fransisco (1979)MATHGoogle Scholar
  14. 14.
    Kvarnström, J., Doherty, P.: TALplanner: A temporal logic based forward chaining planner. Annals of Mathematics and Artificial Intelligence 30, 119–169 (2000)CrossRefMATHGoogle Scholar
  15. 15.
    Long, D., Fox, M.: Efficient implementation of the plan graph in STAN. Journal of Artificial Intelligence Research 10, 87–115 (1999)MATHGoogle Scholar
  16. 16.
    Bonet, B., Geffner, H.: Heuristic search planner 2.0. AI Magazine 22, 77–80 (2001)Google Scholar
  17. 17.
    Steenhuisen, J.R., Witteveen, C.: Plan coordination for durative tasks. In: Salido, M.A., Garrido, A., Bartak, R. (eds.) Proceedings of the Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems (COPLAS), pp. 73–80 (2007)Google Scholar
  18. 18.
    Chetan, Y., Zhang, Y., Witteveen, C.: Performance of coordination mechanisms (published, 2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • J. Renze Steenhuisen
    • 1
  • Cees Witteveen
    • 1
  • Yingqian Zhang
    • 1
  1. 1.Faculty of Electrical Engineering, Mathematics and Computer ScienceDelft University of TechnologyDelftThe Netherlands

Personalised recommendations