This editorial of the special issue “Representing, Processing, and Learning Preferences:
Theoretical and Practical Challenges” surveys past and ongoing research on preferences in …

The paper presents a focused survey about the presence and the use of the concept of
“preferences” in Artificial Intelligence. Preferences are a central concept for decision making …

The ability to effectively reason in the presence of qualitative preferences on literals or
formulas is a central issue in Artificial Intelligence. In the last few years, two procedures have …

The aggregation of generic items into coalitions leads to the creation of sets of homogenous
entities. In this paper we accomplish this for an input set of arguments, and the result is a …

Soft constraint formalisms are an abstract representation of Constraint Satisfaction Problems
(CSPs): the set of preferences is now parametric, often forming (a variety of) an absorptive …

Decision making is required by many tasks, such as shopping, nowadays assisted by
software systems, and providing support to the decision making process is a feature that …

Preferences have been widely studied in several areas including computer science, as they
play an important role in many computational tasks, such as decision making support …

This paper introduces CLEO, a novel preference elicitation algorithm capable of
recommending complex objects in hybrid domains, characterized by both discrete and …

Preferences and uncertainty are common in many real-life problems. In this article, we focus
on bipolar preferences and uncertainty modelled via uncontrollable variables, and we …

Artificial intelligence largely relies on bounds on differences (BoDs) to model binary
constraints regarding different dimensions, such as time, space, costs, and calories …