Automated Negotiations Based on Monotonic Tree Representations

  • Katsuhide FujitaEmail author
Part of the Studies in Computational Intelligence book series (SCI, volume 596)


Automated negotiations occur when a negotiating function is performed among intelligent agents. Although current human-to-human negotiation appears to involve multiple extremely complex issues, each automated negotiation setting is simple. In particular, the structure of issues is independent and flat in the existing automated negotiation framework. In this paper, we propose realistic negotiation frameworks for non-monotonic utility functions. The monotonicity of the utility functions is an important characteristic because if the utility function is monotonic, the issues are independent. When the issues are independent, it is useful to separate them and reach a distinct agreement for each sequentially. In addition, we propose an automated mediation protocol for multiple non-monotonic issue negotiations. This mediation protocol consists of the communications between agents and the mediator. The procedures of the mediation protocol include recognizing related issues, announcement, bidding, awarding, and expediting. We experimentally demonstrate that the proposed method results in good outcomes and greater scalability. In addition, we demonstrate that a suitable mediation strategy leads to better outcomes and scalability.


Automated multi-issue negotiation Agreement technology Monotonic utility function 


  1. 1.
    An, B., Lesser, V.R., Irwin, D., Zink, M.: Automated negotiation with decommitment for dynamic resource allocation in cloud computing. In: Proceedings of the 9th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2010), pp. 981–988 (2010)Google Scholar
  2. 2.
    Boutilier, C., Brafman, R.I., Domshlak, C., Hoos, H.H., Poole, D.: CP-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements. Artif. Intell. Res. 21, 135–191 (2004)MathSciNetzbMATHGoogle Scholar
  3. 3.
    Chevaleyre, Y., Endriss, U., Maudet, N.: Tractable negotiation in tree-structured domains. In: Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS2006), pp. 362–369 (2006)Google Scholar
  4. 4.
    Faratin, P., Sierra, C., Jennings, N.R.: Using similarity criteria to make issue trade-offs in automated negotiations. Artif. Intell. 142, 205–237 (2002)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Fujita, K., Ito, T., Klein, M.: An approach to scalable multi-issue negotiation: decomposing the contract space. Comput. Intell. (2012). doi: 10.1111/j.1467-8640.2012.00462.x CrossRefMathSciNetGoogle Scholar
  6. 6.
    Fujita, K., Ito, T., Klein, M.: A secure and fair protocol that addresses weaknesses of the Nash bargaining solution in nonlinear negotiation. Group Decis. Negot. 21, 29–47 (2012)CrossRefGoogle Scholar
  7. 7.
    Fujita, K., Ito, T., Klein, M.: Efficient issue-grouping approach for multiple interdependent issues negotiation between exaggerator agents. Decis. Support Syst. (2013). doi: 10.1016/j.dss.2013.05.016 CrossRefGoogle Scholar
  8. 8.
    Hindriks, K., Jonker, C., Tykhonov, D.: Eliminating interdependencies between issues for multi-issue negotiation. Cooperative Information Agents X. Lecture Notes in Computer Science, vol. 4149, pp. 301–316. Springer, Berlin (2006)CrossRefGoogle Scholar
  9. 9.
    Ito, T., Hattori, H., Klein, M.: Multi-issue negotiation protocol for agents: exploring nonlinear utility spaces. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI-2007), pp. 1347–1352 (2007)Google Scholar
  10. 10.
    Jennings, N.R., Faratin, P., Lomuscio, A.R., Parsons, S., Sierra, C., Wooldridge, M.: Automated negotiation: prospects, methods and challenges. Int. J. Group Decis. Negot. 10(2), 199–215 (2001)CrossRefGoogle Scholar
  11. 11.
    Jonker, C.M., Robu, V., Treur, J.: An agent architecture for multi-attribute negotiation using incomplete preference information. J. Auton. Agents Multi-Agent Syst. (JAAMAS) 15, 221–252 (2007)CrossRefGoogle Scholar
  12. 12.
    Klein, M., Faratin, P., Sayama, H., Bar-Yam, Y.: Negotiating complex contracts. Group Decis. Negot. 12(2), 58–73 (2003)CrossRefGoogle Scholar
  13. 13.
    Kraus, S.: Strategic Negotiation in Multiagent Environments. Cambridge University Press, Cambridge (2001)zbMATHGoogle Scholar
  14. 14.
    Lai, J., Parkes, D.: Monotone branch-and-bound search for restricted combinatorial auctions. In: Proceedings of the 13th ACM Conference on Electronic Commerce (EC’12), pp. 705–722 (2012)Google Scholar
  15. 15.
    Landsberger, M., Meilijson, I.: Co-monotone allocations, Bickel-Lehmann dispersion and the Arrow-Pratt measure of risk aversion. Ann. Oper. Res. 52, 97–106 (1994)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Lin, R., Kraus, S.: Can automated agents proficiently negotiate with humans? Commun. ACM 53(1), 78–88 (2010)CrossRefGoogle Scholar
  17. 17.
    Lin, R., Kraus, S., Oshrat, Y., Gal, Y.K.: Facilitating the evaluation of automated negotiators using peer designed agents. In: Proceedings of the 24th Association for the Advancement of Artificial Intelligence (AAAI-2010) (2010)Google Scholar
  18. 18.
    Lopez-Carmona, M., Marsa-Maestre, I., Klein, M., Ito, T.: Addressing stability issues in mediated complex contract negotiations for constraint-based, non-monotonic utility spaces. Auton. Agents Multi-Agent Syst. 24(3), 485–535 (2012)CrossRefGoogle Scholar
  19. 19.
    Luo, X., Jennings, N.R., Shadbolt, N., Leung, H., Lee, J.H.: A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments. Artif. Intell. 148, 53–102 (2003)CrossRefGoogle Scholar
  20. 20.
    Luo, X., Lee, J.H.M., Leung, H.F., Jennings, N.R.: Prioritised fuzzy constraint satisfaction problems: axioms, instantiation and validation. Fuzzy Sets Syst. 136, 151–188 (2003)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Malone, T.W., Klein, M.: Harnessing collective intelligence to address global climate change. Innov. J. 2(3), 15–26 (2007)CrossRefGoogle Scholar
  22. 22.
    Ren, F., Zhang, M.: Bilateral single-issue negotiation model considering nonlinear utility and time constraint. Decis. Support Syst. (2013). doi: 10.1016/j.dss.2013.05.018 CrossRefGoogle Scholar
  23. 23.
    Robu, V., Poutre, H.L.: Retrieving the structure of utility graphs used in multi-item negotiation through collaborative filtering of aggregate buyer preferences. In: Proceedings of the 2nd International Workshop on Rational, Robust, and Secure Negotiations in Multi-Agent Systems (RRS-2006) (2006)Google Scholar
  24. 24.
    Robu, V., Somefun, D.J.A., Poutre, J.L.: Modeling complex multi-issue negotiations using utility graphs. In: Proceedings of the 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2005), pp. 280–287 (2005)Google Scholar
  25. 25.
    Rosenschein, J.S., Zlotkin, G.: Rules of Encounter. MIT Press, Cambridge (1994)zbMATHGoogle Scholar
  26. 26.
    Sandholm, T.W.: Distributed rational decision making. In: Weiss, G. (ed.) Multi-Agent Systems. MIT Press, Cambridge (1998)Google Scholar
  27. 27.
    Smith, R.G.: The contract net protocol: high-level communication and control in a distributed problem solver. IEEE Trans. Comput. 29(12), 1104–1113 (1980)CrossRefGoogle Scholar

Copyright information

© Springer Japan 2015

Authors and Affiliations

  1. 1.Department of Computer and Information SciencesTokyo University of Agriculture and TechnologyTokyoJapan

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