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A framework for the interleaving of execution and planning for dynamic tasks by multiple agents

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From Reaction to Cognition (MAAMAW 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 957))

Abstract

The subject of multi-agent planning has been of continuing concern in Distributed Artificial Intelligence (DAI). In this paper, we suggest an approach to the interleaving of execution and planning for dynamic tasks by groups of multiple agents. Agents are dynamically assigned individual tasks that together achieve some dynamically changing global goal. Each agent solves (constructs the plan for) its individual task, then the local plans are merged to determine the next activity step of the entire group in its attempt to accomplish the global goal. Individual tasks may be changed during execution (due to changes in the global goal).

The suggested approach reduces overall planning time and derives a plan that approximates the optimal global plan that would have been derived by a central planner.

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References

  1. D. Chapman. Planning for conjunctive goals. Artificial Intelligence, 32(3):333–377, July 1987.

    Article  Google Scholar 

  2. D. Corkill. Hierarchical planning in a distributed environment. In Proceedings of the Sixth International Joint Conference on Artificial Intelligence, pages 168–175, Tokyo, August 1979.

    Google Scholar 

  3. E. H. Durfee and V. R. Lesser. Using partial global plans to coordinate distributed problem solvers. In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, pages 875–883, Milan, 1987.

    Google Scholar 

  4. E. H. Durfee and V. R. Lesser. Negotiating task decomposition and allocation using partial global planning. In Les Gasser and Michael N. Huhns, editors, Distributed Artificial Intelligence, Vol. II, pages 229–243. Morgan Kaufmann, San Mateo, California, 1989.

    Google Scholar 

  5. Edmund H. Durfee. Coordination of Distributed Problem Solvers. Kluwer Academic Publishers, Boston, 1988.

    Google Scholar 

  6. E. Ephrati and J. S. Rosenschein. Distributed Consensus Mechanisms for Self-interested Heterogeneous Agents. In First International Conference on Intelligent and Cooperative Information Systems, pages 71–79, Rotterdam, The Netherlands, May 1993.

    Google Scholar 

  7. E. Ephrati and J. S. Rosenschein. Reaching agreement through partial revelation of preferences. In Proceedings of the Tenth European Conference on Artificial Intelligence, pages 229–233, Vienna, Austria, August 1992.

    Google Scholar 

  8. J. J. Finger. Exploiting Constraints in Design Synthesis. PhD thesis, Stanford University, Stanford, CA, 1986.

    Google Scholar 

  9. D. E. Foulser, M. Li, and Q. Yang. Theory and algorithms for plan merging. Artificial Intelligence, 57:143–181, 1992.

    Article  Google Scholar 

  10. Matthew J. Katz and J. S. Rosenschein. Verifying plans for multiple agents. Journal of Experimental and Theoretical Artificial Intelligence, 5:39–56, 1993.

    Google Scholar 

  11. R. E. Korf. Planning as search: A quantitative approach. Artificial Intelligence, 33:65–88, 1987.

    Article  Google Scholar 

  12. A. L. Lansky. Localized search for controlling automated reasoning. In Proceedings of the Workshop on Innovative Approaches to Planning, Scheduling and Control, pages 115–125, San Diego, California, November 1990.

    Google Scholar 

  13. D. S. Nau, Q. Yang, and J. Hendler. Optimization of multiple-goal plans with limited interaction. In Proceedings of the Workshop on Innovative Approaches to Planning, Scheduling and Control, pages 160–165, San Diego, California, November 1990.

    Google Scholar 

  14. R. P. Pope, S. E. Conry, and R. A. Mayer. Distributing the planning process in a dynamic environment. In Proceedings of the Eleventh International Workshop on Distributed Artificial Intelligence, pages 317–331, Glen Arbor, Michigan, February 1992.

    Google Scholar 

  15. Reid G. Smith. A Framework for Problem Solving in a Distributed Processing Environment. PhD thesis, Stanford University, 1978.

    Google Scholar 

  16. G. J. Sussman. A Computational Model of Skill Acquisition. American Elsevier, New York, 1975.

    Google Scholar 

  17. W. Vickrey. Counterspeculation, auctions and competitive sealed tenders. Journal of Finance, 16:8–37, 1961.

    Google Scholar 

  18. Frank von Martial. Multiagent plan relationships. In Proceedings of the Ninth International Workshop on Distributed Artificial Intelligence, pages 59–72, Rosario Resort, Eastsound, Washington, September 1989.

    Google Scholar 

  19. Frank von Martial. Coordination of plans in multiagent worlds by taking advantage of the favor relation. In Proceedings of the Tenth International Workshop on Distributed Artificial Intelligence, Bandera, Texas, October 1990.

    Google Scholar 

  20. Q. Yang. A theory of conflict resolution in planning. Artificial Intelligence, 58(1–3):361–393, December 1992.

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Pittsburgh, Pittsburgh, PA

    Eithan Ephrati

  2. Institute of Computer Science, The Hebrew University, Jerusalem, Israel

    Jeffrey S. Rosenschein

Authors
  1. Eithan Ephrati
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  2. Jeffrey S. Rosenschein
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Editor information

Cristiano Castelfranchi Jean-Pierre Müller

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© 1995 Springer-Verlag Berlin Heidelberg

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Ephrati, E., Rosenschein, J.S. (1995). A framework for the interleaving of execution and planning for dynamic tasks by multiple agents. In: Castelfranchi, C., Müller, JP. (eds) From Reaction to Cognition. MAAMAW 1993. Lecture Notes in Computer Science, vol 957. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027061

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  • DOI: https://doi.org/10.1007/BFb0027061

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60155-5

  • Online ISBN: 978-3-540-49532-1

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