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Learning the Structure of Utility Graphs Used in Multi-issue Negotiation through Collaborative Filtering

Preliminary Version
  • Valentin Robu
  • Han La Poutré
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4078)

Abstract

Graphical utility models represent powerful formalisms for modeling complex agent decisions involving multiple issues [2]. In the context of negotiation, it has been shown [10] that using utility graphs enables reaching Pareto-efficient agreements with a limited number of negotiation steps, even for high-dimensional negotiations involving complex complementarity/ substitutability dependencies between multiple issues. This paper considerably extends the results of [10], by proposing a method for constructing the utility graphs of buyers automatically, based on previous negotiation data. Our method is based on techniques inspired from item-based collaborative filtering, used in online recommendation algorithms. Experimental results show that our approach is able to retrieve the structure of utility graphs online, with a high degree of accuracy, even for highly non-linear settings and even if a relatively small amount of data about concluded negotiations is available.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Valentin Robu
    • 1
  • Han La Poutré
    • 1
  1. 1.CWIDutch National Research Center for Mathematics and Computer ScienceAmsterdamThe Netherlands

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