Aim of the workshop

Following the workshop DA2PL'2012, organized in University of Mons, the second edition of the DA2PL workshop aims at bringing together researchers involved in Preference Modeling and Preference Learning and identify research challenges at the crossroad of both research fields.

The need for search engines able to select and rank order the pages most relevant to a user’s query has emphasized the issue of learning the user’s preferences and interests in an adequate way. That is to say, on the basis of little information on the person who queries the Web, and, in almost no time. Recommender systems also rely on efficient preference learning.

On the other hand, preference modeling has been an auxiliary discipline related to Multicriteria decision aiding for a long time. Methods for eliciting preference models, including learning by examples, are a crucial issue in this field.

It is quite natural to think and to observe in practice that preference modeling and learning are two fields that have things to say to one another. It is the main goal of the present workshop to bring together researchers involved in those disciplines, in order to identify research issues in which cross-fertilization is already at work or can be expected. Communications related to successful usage of explicit preference models in preference learning are especially welcome as well as communications devoted to innovative preference learning methods in MCDA. The programme of the workshop will consist of three or four invited lectures and about 15 selected research communications.


This workshop is co-organized by Ecole Centrale Paris and University of Mons in the framework of the GDRI “Algorithmic Decision Theory”, which is recognized and supported by CNRS (France), FNRS (Belgium), FNR (Luxemburg). The workshop is also supported by the French GDR RO (CNRS) - Pôle : Décision : Modélisation, Prévision, Evaluation (DMPE)