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)


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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