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Measuring the Performance of Online Opponent Models in Automated Bilateral Negotiation

  • Tim Baarslag
  • Mark Hendrikx
  • Koen Hindriks
  • Catholijn Jonker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7691)

Abstract

An important aim in bilateral negotiations is to achieve a win-win solution for both parties; therefore, a critical aspect of a negotiating agent’s success is its ability to take the opponent’s preferences into account. Every year, new negotiation agents are introduced with better learning techniques to model the opponent. Our main goal in this work is to evaluate and compare the performance of a selection of state-of-the-art online opponent modeling techniques in negotiation, and to determine under which circumstances they are beneficial in a real-time, online negotiation setting. Towards this end, we provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. This results in better insight into the performance of opponent models, and allows us to pinpoint well-performing opponent modeling techniques that did not receive much previous attention in literature.

Keywords

Negotiation Opponent Model Performance Quality Measures 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Tim Baarslag
    • 1
  • Mark Hendrikx
    • 1
  • Koen Hindriks
    • 1
  • Catholijn Jonker
    • 1
  1. 1.Interactive Intelligence GroupDelft University of TechnologyDelftThe Netherlands

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