The Second Automated Negotiating Agents Competition (ANAC2011)

  • Katsuhide Fujita
  • Takayuki Ito
  • Tim Baarslag
  • Koen Hindriks
  • Catholijn Jonker
  • Sarit Kraus
  • Raz Lin
Part of the Studies in Computational Intelligence book series (SCI, volume 435)

Abstract

In May 2011, we organized the Second International Automated Negotiating Agents Competition (ANAC2011) in conjunction with AAMAS 2011. ANAC is an international competition that challenges researchers to develop a successful automated negotiator for scenarios where there is incomplete information about the opponent. One of the goals of this competition is to help steer the research in the area of bilateral multi-issue negotiations, and to encourage the design of generic negotiating agents that are able to operate in a variety of scenarios. Eighteen teams from seven different institutes competed in ANAC2011. This chapter describes the participating agents and the setup of the tournament, including the different negotiation scenarios that were used in the competition. We report on the results of the qualifying and final round of the tournament.

Keywords

Discount Factor Pareto Frontier Outcome Space Negotiation Protocol Final Round 
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.
    Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T. (eds.): New Trends in Agent-Based Complex Automated Negotiations. SCI, vol. 383. Springer, Heidelberg (2012)Google Scholar
  2. 2.
    Aumann, R.J., Hart, S. (eds.): Handbook of Game Theory with Economic Applications, vol. 1. Elsevier (March 1992)Google Scholar
  3. 3.
    Bazerman, M.H., Neale, M.A.: Negotiator rationality and negotiator cognition: The interactive roles of prescriptive and descriptive research. In: Young, H.P. (ed.) Negotiation Analysis, pp. 109–130. The University of Michigan Press (1992)Google Scholar
  4. 4.
    Erev, I., Roth, A.: Predicting how people play games: Reinforcement learning in experimental games with unique, mixed strategy equilibrium. American Economic Review 88(4), 848–881 (1998)Google Scholar
  5. 5.
    Faratin, P., Sierra, C., Jennings, N.R.: Negotiation decision functions for autonomous agents. Int. Journal of Robotics and Autonomous Systems 24(3-4), 159–182 (1998)CrossRefGoogle Scholar
  6. 6.
    Faratin, P., Sierra, C., Jennings, N.R.: Using similarity criteria to make negotiation trade-offs. Journal of Artificial Intelligence 142(2), 205–237 (2003)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Fatima, S.S., Wooldridge, M., Jennings, N.R.: Multi-issue negotiation under time constraints. In: AAMAS 2002: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 143–150. ACM, New York (2002)CrossRefGoogle Scholar
  8. 8.
    Ito, T., Hattori, H., Klein, M.: Multi-issue negotiation protocol for agents: Exploring nonlinear utility spaces (2007)Google Scholar
  9. 9.
    Jonker, C.M., Robu, V., Treur, J.: An agent architecture for multi-attribute negotiation using incomplete preference information. Journal of Autonomous Agents and Multi-Agent Systems 15(2), 221–252 (2007)CrossRefGoogle Scholar
  10. 10.
    Kraus, S.: Strategic Negotiation in Multiagent Environments. MIT Press (October 2001)Google Scholar
  11. 11.
    Kraus, S., Wilkenfeld, J., Zlotkin, G.: Multiagent negotiation under time constraints. Artificial Intelligence 75(2), 297–345 (1995)MathSciNetMATHCrossRefGoogle Scholar
  12. 12.
    Lin, R., Kraus, S., Tykhonov, D., Hindriks, K., Jonker, C.M.: Supporting the Design of General Automated Negotiators. In: Ito, T., Zhang, M., Robu, V., Fatima, S., Matsuo, T., Yamaki, H. (eds.) Innovations in Agent-Based Complex Automated Negotiations. SCI, vol. 319, pp. 69–87. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  13. 13.
    McKelvey, R.D., Palfrey, T.R.: An experimental study of the centipede game. Econometrica 60(4), 803–836 (1992)MATHCrossRefGoogle Scholar
  14. 14.
    Osborne, M.J., Rubinstein, A.: Bargaining and Markets (Economic Theory, Econometrics, and Mathematical Economics). Academic Press (April 1990)Google Scholar
  15. 15.
    Osborne, M.J., Rubinstein, A.: A Course in Game Theory. MIT Press (1994)Google Scholar
  16. 16.
    Rubinstein, A.: Perfect equilibrium in a bargaining model. Econometrica 50(1), 97–109 (1982)MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Katsuhide Fujita
    • 1
  • Takayuki Ito
    • 2
  • Tim Baarslag
    • 3
  • Koen Hindriks
    • 3
  • Catholijn Jonker
    • 3
  • Sarit Kraus
    • 4
    • 5
  • Raz Lin
    • 4
  1. 1.School of EngineeringThe University of TokyoTokyoJapan
  2. 2.Techno-Business Administration (MTBA)Nagoya Institute of TechnologyNagoyaJapan
  3. 3.Man Machine Interaction GroupDelft University of TechnologyDelftThe Netherlands
  4. 4.Computer Science DepartmentBar-Ilan UniversityBar-IlanIsrael
  5. 5.Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA

Personalised recommendations