Autonomous Agents and Multi-Agent Systems

, Volume 10, Issue 2, pp 165–205 | Cite as

Efficient Management of Multi-Linked Negotiation Based on a Formalized Model

  • Xiaoqin Zhang
  • Victor Lesser
  • Sherief Abdallah


A Multi-linked negotiation problem occurs when an agent needs to negotiate with multiple other agents about different subjects (tasks, conflicts, or resource requirements), and the negotiation over one subject has influence on negotiations over other subjects. The solution of the multi-linked negotiations problem will become increasingly important for the next generation of advanced multi-agent systems. However, most current negotiation research looks only at a single negotiation and thus does not present techniques to manage and reason about multi-linked negotiations. In this paper, we first present a technique based on the use of a partial-order schedule and a measure of the schedule, called flexibility, which enables an agent to reason explicitly about the interactions among multiple negotiations. Next, we introduce a formalized model of the multi-linked negotiation problem. Based on this model, a heuristic search algorithm is developed for finding a near-optimal ordering of negotiation issues and their parameters. Using this algorithm, an agent can evaluate and compare different negotiation approaches and choose the best one. We show how an agent uses this technology to effectively manage interacting negotiation issues. Experimental work is presented which shows the efficiency of this approach.


multiple related negotiations agent reasoning and control conflict resolution performance optimization 


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  1. W.Conen and T.Sandholm, “Preference elicitation in combinatorial auctions: Extended abstract”, inACM Conference on Electronic Commerce (ACM-EC), Tampa, FL, October 14--17, 2001.Google Scholar
  2. M.Frank, A.Bugacov, J.Chen, G.Dakin, P.Szekely, and B.Neches, “The marbles manifesto: A definition and comparison of cooperative negotiation schemes for distributed resource allocation”, inAAAI Fall 2001 Symposium on Negotiation Methods for Autonomous Cooperative Systems2001.Google Scholar
  3. Fujishima, Y., Leyton-Brown, K., Shoham, Y. 1999“Taming the computational complexity of combinatorial auctions Optimal and approximate approaches”. in Proceedings of International Joint Conference on Artificial Intelligence IJCAI’99StockholmSwedenGoogle Scholar
  4. B. Horling, R. Vincent, and V. Lesser, “Multi-agent system simulation framework”. in 16th IMACS World Congress 2000 on Scientific Computation, Applied Mathematics and Simulation. EPFL, August 2000.Google Scholar
  5. B. Horling, R. Vincent, R. Mailler, J. Shen, R. Becker, K. Rawlins, and V. Lesser, “Distributed sensor network for real time tracking”. in Proceedings of the 5th International Conference on Autonomous Agents, ACM Press: Montreal pp. 417–424, June 2001Google Scholar
  6. L. Hunsberger and B. J. Grosz, “A combinatorial auction for collaborative planning”, in Proceedings of the Fourth International Conference on Multi-Agent Systems (ICMAS-2000), 2000.Google Scholar
  7. J. J. Moder, C. R. Phillips, and E. W. Davis. Project Management with CPM, PERT and Precedence Diagramming. Blitz Pub Co, 1995.Google Scholar
  8. A. Pritsker, “Gert networks graphical evaluation and review technique”. The Production Engineer, 1968.Google Scholar
  9. T. Sandholm and V. Lesser, “On automated contracting in multi-enterprise manufacturing”. in Proceedings of the Improving Manufacturing Performance in a Distributed Enterprise: Advanced Systems and Tools.Google Scholar
  10. T.Sandholm and V.Lesser, “Issues in automated negotiation and electronic commerce: Extending the contract net framework”, inProceedings of the First International Conference on Multi-Agent Systems (ICMAS95)1995.Google Scholar
  11. T. Sandholm and S. Suri, “Improved algorithms for optimal winner determination in combinatorial auctions and generalizations”, in National Conference on Artificial Intelligence (AAAI), 2000.Google Scholar
  12. Sen, S., Durfee, E.H. 1998“A formal study of distributed meeting scheduling”Group Decision and Negotiation72651998Google Scholar
  13. R.G. Smith, “The contract net protocol: High-level communication and control in a distributed problem solver”,IEEE Transactions on Computers1980.Google Scholar
  14. Wagner, T., Lesser, V. 2002“Evolving real-time local agent control for large-scale mas”Meyer, J.Tambe, M. eds. Lecture Notes in Artificial IntelligenceSpringer-VerlagBerlinIntelligent Agents VIII (Proceedings of ATAL-01)Google Scholar
  15. W. Walsh, M. Wellman, and F. Ygge, “Combinatorial auctions for supply chain formation”, in Second ACM Conference on Electronic Commerce, 2000.Google Scholar
  16. X. Zhang, Sophisticated Negotiation In Multi-Agent Systems. Ph.D. thesis, University of Massachusetts: Amherst, 2002.Google Scholar
  17. X. Zhang, V. Lesser, and R. Podorozhny, “New results on cooperative, multistep negotiation over a multi-dimensional utility function” in AAAI Fall 2001 Symposium on Negotiation Methods for Autonomous Cooperative Systems, pp. 1–10, 2001.\widetilde xqzhang/pub/ Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Xiaoqin Zhang
    • 1
  • Victor Lesser
    • 2
  • Sherief Abdallah
    • 2
  1. 1.Department of Computer and Information ScienceUniversity of Massachusetts at DartmouthUSA
  2. 2.Department of Computer ScienceUniversity of Massachusetts at AmherstUSA

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