AgentK: Compromising Strategy based on Estimated Maximum Utility for Automated Negotiating Agents

  • Shogo Kawaguchi
  • Katsuhide Fujita
  • Takayuki Ito
Part of the Studies in Computational Intelligence book series (SCI, volume 383)


The Automated Negotiation Agents Competition (ANAC-10) was held and our agent won the tournament. Our agent estimates the alternatives the opponent will offer based on the history of the opponent’s offers. In addition, our agent tries to compromise to the estimated maximum utility of the opponent by the end of the negotiation. Also, we modify the basic strategy to not exceed the limit of compromise when the opponent is uncooperative. We can adjust the speed of compromise depending on the negotiation. We introduce the new ratio(t) to control our agent’s actions at the final phase. With this improvement, our agents try to reach agreement when the opponent’s proposal is closer to our estimated maximum values. The main reason our agent outperforms the others is its ability to reach a last-minute agreement as often as possible.


Basic Strategy Utility Space Automate Negotiation Negotiation Round Nagoya Institute 
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.


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  1. 1.
    Baarslag, T., Hindriks, K., Jonker, C., Kraus, S., Lin, R.: The First Automated Negotiating Agents Competition (ANAC 2010). In: Ito, T., et al. (eds.) New Trends in Agent-Based Complex Automated Negotiations. SCI, vol. 383, pp. 113–135. Springer, Heidelberg (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Shogo Kawaguchi
    • 1
  • Katsuhide Fujita
    • 2
  • Takayuki Ito
    • 3
  1. 1.Department of Computer ScienceNagoya Institute of TechnologyNagoyaJapan
  2. 2.Department of Computer Science and EngineeringNagoya Institute of TechnologyNagoyaJapan
  3. 3.School of Techno-Business AdministrationNagoya Institute of TechnologyNagoyaJapan

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