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Offer Evaluation and Trade-Off Making in Automated Negotiation Based on Intuitionistic Fuzzy Constraints

  • Jieyu Zhan
  • Xudong Luo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9862)

Abstract

In automated negotiation, one of crucial problems is how a negotiating agent evaluates the acceptability of an offer. Most models mainly use two kinds of evaluation methods: (i) linear utility functions that depend on issues, and (ii) nonlinear utility functions that depend on crisp constraints. However, in real life, it is hard for human users to input so much and so accurate information that these evaluation methods require. To this end, this paper proposes a new approach for offer evaluation where human users are allowed to input indeterminate information. More specifically, we propose a framework of prioritised intuitionistic fuzzy constraint satisfaction problems for modelling agent’s goals. Moreover, we take both satisfaction degree and dissatisfaction degree into consideration when calculating an agent’s acceptability of an offer. Finally, we discuss how to make trade-offs via similarity measure based on intuitionistic fuzzy criteria functions.

Keywords

Multi-issue automated negotiation Intuitionistic fuzzy set Fuzzy constraint satisfaction Similarity Trade-off 

Notes

Acknowledgments

This research is supported by the Bairen Plan of Sun Yat-sen University and the National Fund of Social Science (No. 13BZX066).

References

  1. 1.
    Amgoud, L., Vesic, S.: A formal analysis of the outcomes of argumentation-based negotiations. In: Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems, pp. 1237–1238 (2011)Google Scholar
  2. 2.
    Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986)MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Baarslag, T., Fujita, K., Gerding, E.H., Hindriks, K., Ito, T., Jennings, N.R., Jonker, C., Kraus, S., Lin, R., Robu, V., et al.: Evaluating practical negotiating agents: results and analysis of the 2011 international competition. Artif. Intell. 198, 73–103 (2013)CrossRefGoogle Scholar
  4. 4.
    Baarslag, T., Hindriks, K., Jonker, C.: Acceptance conditions in automated negotiation. In: Ito, T., Zhang, M., Robu, V., Matsuo, T. (eds.) Complex Automated Negotiations: Theories, Models, and Software Competitions. SCI, vol. 435, pp. 95–111. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Cao, M., Luo, X., Luo, X.R., Dai, X.: Automated negotiation for e-commerce decision making: a goal deliberated agent architecture for multi-strategy selection. Decis. Support Syst. 73, 1–14 (2015)CrossRefGoogle Scholar
  6. 6.
    Davis, R., Smith, R.G.: Negotiation as a metaphor for distributed problem solving. Artif. Intell. 20(1), 63–109 (1983)CrossRefGoogle Scholar
  7. 7.
    Faratin, P., Sierra, C., Jennings, N.R.: Using similarity criteria to make issue trade-offs in automated negotiations. Artif. Intell. 142(2), 205–237 (2002)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Fujita, K., Ito, T., Klein, M.: Efficient issue-grouping approach for multiple interdependent issues negotiation between exaggerator agents. Decis. Support Syst. 60, 10–17 (2014)CrossRefGoogle Scholar
  9. 9.
    Hadfi, R., Ito, T.: On the complexity of utility hypergraphs. In: Fukuta, N., Ito, T., Zhang, M., Fujita, K., Robu, V. (eds.) Recent Advances in Agent-based Complex Automated Negotiation. SCI, vol. 638, pp. 89–105. Springer, Heidelberg (2016)CrossRefGoogle Scholar
  10. 10.
    Hadidi, N., Dimopoulos, Y., Moraitis, P.: Argumentative alternating offers. In: Proceedings of the 9th International Conference on Autonomous Agents and Multi-agent Systems, pp. 441–448 (2010)Google Scholar
  11. 11.
    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, pp. 1347–1352 (2007)Google Scholar
  12. 12.
    Jennings, N.R., Faratin, P., Lomuscio, A.R., Parsons, S., Wooldridge, M.J., Sierra, C.: Automated negotiation: prospects, methods and challenges. Group Decis. Negot. 10(2), 199–215 (2001)CrossRefGoogle Scholar
  13. 13.
    Klein, M., Faratin, P., Sayama, H., Bar-Yam, Y.: Negotiating complex contracts. Group Decis. Negot. 12(2), 111–125 (2003)CrossRefMATHGoogle Scholar
  14. 14.
    Kumar, V.: Algorithms for constraint-satisfaction problems: a survey. AI Mag. 13(1), 32 (1992)Google Scholar
  15. 15.
    Le, D.T., Zhang, M., Ren, F.: A relaxation strategy with fuzzy constraints for supplier selection in a power market. In: Bai, Q., Ren, F., Zhang, M., Ito, T., Tang, X. (eds.) Smart Modeling Simulation for Complex Systems: Practice and Theory. SCI, vol. 564, pp. 83–97. Springer, Heidelberg (2015)Google Scholar
  16. 16.
    Luo, X., Jennings, N.R., Shadbolt, N.: Acquiring user tradeoff strategies and preferences for negotiating agents: a default-then-adjust method. Int. J. Hum.-Comput. Stud. 64(4), 304–321 (2006)CrossRefGoogle Scholar
  17. 17.
    Luo, X., Jennings, N.R., Shadbolt, N., Leung, H.-F., Lee, J.H.-M.: A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments. Artif. Intell. 148(1), 53–102 (2003)MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    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(2), 151–188 (2003)MathSciNetCrossRefMATHGoogle Scholar
  19. 19.
    Luo, X., Miao, C., Jennings, N.R., He, M., Shen, Z., Zhang, M.: KEMNAD: a knowledge engineering methodology for negotiating agent development. Comput. Intell. 28(1), 51–105 (2012)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Marey, O., Bentahar, J., Dssouli, R., Mbarki, M.: Measuring and analyzing agents uncertainty in argumentation-based negotiation dialogue games. Expert Syst. Appl. 41(2), 306–320 (2014)CrossRefGoogle Scholar
  21. 21.
    Marey, O., Bentahar, J., En-Nouaary, A.: On the measurement of negotiation dialogue games. In: Proceedings of the International Conference on Intelligent Software Methodologies, Tools and Techniques, pp. 223–244 (2009)Google Scholar
  22. 22.
    Mbarki, M., Marey, O., Bentahar, J., Sultan, K.: Agent types and adaptive negotiation strategies in argumentation-based negotiation. In: Proceedings of the 26th International Conference on Tools with Artificial Intelligence, pp. 485–492 (2014)Google Scholar
  23. 23.
    Rahwan, I., Ramchurn, S.D., Jennings, N.R., Mcburney, P., Parsons, S., Sonenberg, L.: Argumentation-based negotiation. Knowl. Eng. Rev. 18(04), 343–375 (2003)CrossRefGoogle Scholar
  24. 24.
    Ruttkay, Z.: Fuzzy constraint satisfaction. In: Proceedings of the Third IEEE Conference on Fuzzy Systems, pp. 1263–1268 (1994)Google Scholar
  25. 25.
    Zadeh, L.A.: Information and control. Fuzzy Sets 8(3), 338–353 (1965)MathSciNetGoogle Scholar
  26. 26.
    Zhan, J., Zhang, M., Ren, F., Luo, X.: A negotiation-based model for policy generation. In: Proceedings of the 8th International Workshop on Agent-Based Complex Automated Negotiation, pp. 50–57 (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of Logic and Cognition, Department of PhilosophySun Yat-sen UniversityGuangzhouChina

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