Advertisement

A System for Analysis of Multi-Issue Negotiation

  • Tibor Bosse
  • Catholijn M. Jonker
  • Lourens van der Meij
  • Valentin Robu
  • Jan Treur
Part of the Whitestein Series in Software Agent Technologies book series (WSSAT)

Abstract

This paper presents a System for Analysis of Multi-Issue Negotiation (SAMIN). The agents in this system conduct one-to-one negotiations, in which the values across multiple issues are negotiated on simultaneously. It is demonstrated how the system supports both automated negotiation (i.e., conducted by a software agent) and human negotiation (where humans specify their bids). To analyse such negotiation processes, the user can enter any formal property deemed useful into the system and use the system to automatically check this property in given negotiation traces. Furthermore, it is shown how, compared to fully closed negotiation, the efficiency of the reached agreements may be improved, either by using incomplete preference information revealed by the negotiation partner or by incorporating a heuristic, through which an agent uses the history of the opponent’s bids in order to guess his preferences.

Keywords

Multiagent System Negotiation Process None None Software Agent Preference Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Bosse, T., Jonker, C. and Treur, J., Formalisation of Dynamic Properties of Multi-Issue Negotiations. Vrije Universiteit Amsterdam, Department of Artificial Intelligence. Technical Report, 2004.Google Scholar
  2. [2]
    Faratin, P., Sierra, C., and Jennings, N.R., Negotiation decision functions for autonomous agents. In: International Journal of Robotics and Autonomous Systems, vol. 24(3–4), 1998, pp. 159–182.Google Scholar
  3. [3]
    Hyder, E.B., Prietula, M.J., and Weingart, L.R., Getting to Best: Efficiency versus Optimality in Negotiation, In: Cognitive Science, vol. 24(2), 2000, pp. 169–204.CrossRefGoogle Scholar
  4. [4]
    Jonker, C.M., Treur, J., An Agent Architecture for Multi-Attribute Negotiation. In: B. Nebel (ed.), Proceedings of the 17th International Joint Conference on AI, IJCAI’01, 2001, pp. 1195–1201.Google Scholar
  5. [5]
    Jonker, C.M., and Treur, J., Compositional Verification of Multi-Agent Systems: a Formal Analysis of Pro-activeness and Reactiveness. International Journal of Cooperative Information Systems, vol. 11, 2002, pp. 51–92.CrossRefMathSciNetGoogle Scholar
  6. [6]
    Klein, M., Faratin, P., Sayama, H., and Bar-Yam, Y., (2001), Negotiating Complex Contracts. Paper 125 of the Center for eBusines@MIT. http://ebusiness.mit.edu.Google Scholar
  7. [7]
    Kowalczyk, R, Bui, V., On Constraint-Based Reasoning in e-Negotiation Agents. In: Dignum, F, and Cortés, U., (eds.), Agent-Mediated Electronic Commerce III, Current Issues in Agent-Based Electronic Commerce Systems, Lecture Notes in Computer Science, vol. 2003, Springer — Verlag, pp. 31–46.Google Scholar
  8. [8]
    Lomuscio, A.R., Wooldridge, M., and Jennings. N.R., (2000), A classification scheme for negotiation in electronic commerce, In: International Journal of Group Decision and Negotiation, vol. 12(1), January 2003.Google Scholar
  9. [9]
    Pruitt, D.G., Negotiation Behavior, Academic Press, 1981.Google Scholar
  10. [10]
    Raiffa, H., Lectures on Negotiation Analysis, PON Books, Program on Negotiation at Harvard Law School, 513 Pound Hall, Harvard Law School, Cambridge, Mass. 02138, 1996.Google Scholar
  11. [11]
    Rosenschein, J.S., and Zlotkin, G., Rules of Encounter: Designing Conventions for Automated Negotiation among Computers. The MIT Press, Cambridge, MA, 1994.Google Scholar
  12. [12]
    Sandholm, T., Distributed rational decision making, In: Weiss, G., Multi-agent Systems: A Modern Introduction to Distributed Artificial Intelligence, MIT Press, 1999, pp. 201–258.Google Scholar
  13. [13]
    Weingart, L.R., Hyder, E.H., and Prietula, M.J., Knowledge matters: The effect of tactical descriptions on negotiation behavior and outcome. In: Journal of Applied Psychology, vol. 78, 1996, pp. 504–517.Google Scholar
  14. [14]
    Jonker, C., Robu, V. — “Automated multi-attribute negotiation with efficient use of incomplete preference information”, Proceedings of the 3rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-04), New York, July 2004.Google Scholar
  15. [15]
    Brazier, F.M.T., Jonker, C.M., and Treur, J. “Compositional Design and Reuse of a Generic Agent Model”, Applied Artificial Intelligence Journal, vol. 14, 2000, pp. 491–538.Google Scholar
  16. [16]
    Byde, A., Kay-Yut Chen — “AutONA: A System for Automated Multiple 1-1 Negotiation”, Fourth ACM Conference on Electronic Commerce, pp. 198–199.Google Scholar
  17. [17]
    Faratin, P., Sierra, C. and Jennings, N. Using Similarity Criteria to Make Issue Trade-offs in Automated Negotiations. Journal of Artificial Intelligence vol. 142(2), 2003, pp. 205–237.MathSciNetGoogle Scholar
  18. [18]
    Faratin, P., Sierra, C. and Jennings, N. “Using Similarity Criteria to Make Negotiation Trade-Offs”, Proceedings of ICMAS-2000, Boston, MA., 119–126.Google Scholar
  19. [19]
    Fatima, S. S., Wooldridge, M. and Jennings, N. R.. “Optimal Agendas for Multi-Issue Negotiation”. In Proceedings of the Second International Conference on Autonomous Agents and Multiagent Systems (AAMAS-03), Melbourne, July 2003, pp. 129–136.Google Scholar
  20. [20]
    Fatima, S., Wooldridge, M. and Jennings, N. R.. “Optimal Negotiation Strategies for Agents with Incomplete Information”. In Intelligent Agents VIII, Springer-Verlag LNAI, vol. 2333, pp 377–392, March 2002Google Scholar
  21. [21]
    Raiffa, H. — “The art and science of negotiation”, Harvard University Press, Cambridge, Mass., 1982.Google Scholar

Copyright information

© Birkhäuser Verlag 2005

Authors and Affiliations

  • Tibor Bosse
    • 1
  • Catholijn M. Jonker
    • 2
  • Lourens van der Meij
    • 3
  • Valentin Robu
    • 4
  • Jan Treur
    • 3
  1. 1.Department of Artificial IntelligenceVrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.Nijmegen Institute for Cognition and InformationRadboud Universiteit NijmegenNijmegenThe Netherlands
  3. 3.Vrije Universiteit AmsterdamThe Netherlands
  4. 4.National Center for Mathematics and Computer ScienceCWIAmsterdamThe Netherlands

Personalised recommendations