Graphical models for preference representation: An overview

Publication Type:
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 9858 LNAI pp. 96 - 111
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© Springer International Publishing Switzerland 2016. Representing preferences into a compact structure has become an important research topic. Graphical models are of special interest. Indeed, they facilitate elicitation, exhibit some form of independence, and serve as a basis for solving optimization and dominance queries about choices. The expressiveness of the representation setting and the complexity of answering queries are then central issues for each approach. This paper proposes an extensive overview of the main graphical models for preference representation and provides a comparative survey by emphasizing their main characteristics. We also indicate possible transformations between some of these models. We contrast qualitative models such as CP-nets and TCP-nets with quantitative ones such as GAI networks, UCP-nets, and Marginal utility nets, and advocate π-Pref nets, recently introduced by the authors, as an interesting compromise between the two types of models.
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