Automated Sealed-Bid Negotiation Model for Multi-issue Based on Fuzzy Method

  • Linlan Zhang
  • Haigang Song
  • Xueguang Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5552)


This paper presents an automated sealed-bid design for multi-issue negotiation. In our negotiation model, both agents simultaneously submit their offers to the mediate agent. Each agent has a representation of its desired attributes for a trading commodity using fuzzy linguistic terms. This method is flexible for the agents to offer according to own demand, taking into account the interdependencies between the attributes. It is important to emphasize that proposed bargaining method is carried out under incomplete information, and agents’ information about own parameters are considered completely private. The design can discourage counter-speculation and effectively control fraud and misrepresentation in a certain extent. In addition, using the proposed method of calculating agreed-price, agents can be stimulated to reach an agreement as early as possible. Through a case study, the capabilities of the proposed method are illustrated.


Bargaining Multi-issue negotiation Sealed-bid Membership function 


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  1. 1.
    Maes, R.P., Moukas, A.G.: Agents that Buy and Sell. Communications of the ACM 42(3), 81–91 (1999)CrossRefGoogle Scholar
  2. 2.
    Sandholm, T.: Agents in Electronic Commerce: Component Technologies for Automated Negotiation and Coalition Formation. Autonomous Agents and Multi-Agent Systems 3(1), 73–96 (2000)CrossRefGoogle Scholar
  3. 3.
    Faratin, P., Sierra, C., Jenning, N.R.: Using Similarity Criteria to Make Issue Trade-offs in Automated Negotiations. Artificial Intelligence 142, 205–237 (2002)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Fatima, S.S., Wooldridge, M., Jennings, N.R.: Optimal Negotiation of Multiple Issues in Incomplete Information Settings. In: Proc. of AAMAS 2004, pp. 1080–1087 (2004)Google Scholar
  5. 5.
    Lau, R.Y.K.: Towards Genetically Optimized Multi-agent Multi-issue Negotiations. In: Proc. of HICSS 2005 (2005)Google Scholar
  6. 6.
    Soh, L.K., Li, X.: Adaptive Confidence-based Multi-agent Negotiation Strategy. In: Proc. of AAMAS 2004, pp. 1048–1055 (2004)Google Scholar
  7. 7.
    Klein, M., Faratin, P., Sayama, H., Yam, Y.B.: Protocols for Negotiating Complex Contracts. IEEE Intelligent Systems (2003)Google Scholar
  8. 8.
    Klein, M.: Multi Issue Negotiation Protocol for Agents Exploring Nonlinear Utility Spaces. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, Hyderabad, India (2007)Google Scholar
  9. 9.
    Lin, R.J., Chou, S.T.: Bilateral Multi-issue Negotiations in a Dynamic Environment. In: Proc. of AMEC 2003 (2003)Google Scholar
  10. 10.
    Barbuceanu, M.H., Lo, W.K.: Multi-attribute Utility Theoretic Negotiation for Electronic Commerce. In: Dignum, F.P.M., Cortés, U. (eds.) AMEC 2000. LNCS, vol. 2003, pp. 15–30. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  11. 11.
    Luo, X.D., Jennings, N.R., Shadbolt, N., Leung, H.F., Lee, J.H.: A Fuzzy Constraint Based Model for Bilateral. Multi-issue Negotiations in Semi-competitive Environments. Artificial Intelligence 148, 53–102 (2003)zbMATHGoogle Scholar
  12. 12.
    Bhavsar, V., Boley, H., Yang, L.: A Weighted-tree Similarity Algorithm for Multi-agent Systems in E-business Environments. Computational Intelligence Journal 20(4), 584–602 (2004)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Boley, H., Bhavsar, V.C., Hirtle, D., Singh, A., Sun, Z., Yang, L.: Agent Matcher Search in Weighted, Tree-structured Learning Object Metadata. In: Learning Objects Summit, pp. 29–30. Fredericton (2004)Google Scholar
  14. 14.
    Kebriaei, H., Majd, V.J.: A Simultaneous Multi-attribute Soft-bargaining Design for Bilateral Contracts. Expert Systems with Applications (2008), doi:10.1016/j.eswa.2008.05.003Google Scholar
  15. 15.
    Faratin, P., Sierra, C., Jennings, N.R.: Negotiation Decision Functions for Autonomous Agents. International Journal of Robotics and Autonomous Systems 24(3-4), 159–182 (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Linlan Zhang
    • 1
  • Haigang Song
    • 2
  • Xueguang Chen
    • 1
  1. 1.Institute of Systems EngineeringHuazhong University of Science and TechnologyWuhanChina
  2. 2.Basic Research Service of the Ministry of Science and Technology of the P. R. ChinaBeijingChina

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