In order to represent the preferences of a group of individuals, we introduce Probabilistic CP-
nets (PCP-nets). PCP-nets provide a compact language for representing probability …

The generation of preferences represented as CP-nets for experiments and empirical testing
has typically been done in an ad hoc manner that may have introduced a large statistical …

Modelling preferences has been an active research topic in Artificial Intelligence for more
than fifteen years. Existing formalisms are rich and flexible enough to capture the behaviour …

Conditional preference networks (CP-nets) exploit the power of ceteris paribus rules to
represent preferences over combinatorial decision domains compactly. CP-nets have much …

This paper addresses the problem of combining uncertainty and precision in CP-nets.
Existing approaches extended the network either with probability distribution to manage …

In this paper we provide a general process to create the most K-groups based on incomplete
profiles and conditional preferences. The proposed approach is shown to be a combination …

Résumé La modélisation des préférences par le biais de formalismes de représentation
compacte fait l'objet de travaux soutenus en intelligence artificielle depuis plus d'une …

A Probabilistic Conditional Preference network (PCP-net) provides a compact
representation of preferences characterized with uncertainty. We propose to enrich the …

In this thesis, a new framework for constraint and preference representation and reasoning
is proposed, including the related definitions, algorithms and implementations. A Conditional …

Successful man-machine interaction requires justification and transparency for the behavior
of the machine. Artificial agents now perform a variety of high risk jobs alongside humans …