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AgentK2: 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 435)

Abstract

In the setting of the competition, my utility space is not mutually taught the other agent. Therefore, there is a little information can be used for the strategy construction. In this thesis, it proposes the technique for expecting the best mutual agreement offer that can be get out from the other agent in the future from the statistical information of the value in which the other agent’s proposal is evaluated it’s own utility space.

Keywords

Acceptance Probability Mutual Agreement Utility Space Automate Negotiation Inverse Propor 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Shogo Kawaguchi
    • 1
  • Katsuhide Fujita
    • 1
    • 2
  • Takayuki Ito
    • 1
  1. 1.Nagoya Institute of TechnologyNagoyaJapan
  2. 2.Massachusetts Institute of TechnologyCambridgeU.S.A.

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