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

In recent years, CP-nets have emerged as a useful tool for supporting preference elicitation,
reasoning, and representation. CP-nets capture and support reasoning with qualitative …

Abstract Dung's abstract Argumentation Framework (AF) has emerged as a central
formalism in the area of knowledge representation and reasoning. Preferences in AF allow …

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 …

We present a tutorial introduction to the area of preference handling-one of the core issues
in the design of any system that automates or supports decision making. The main goal of …

Constraining the actions of AI systems is one promising way to ensure that these systems
behave in a way that is morally acceptable to humans. But constraints alone come with …

Decision making is the crucial step in many real applications such as organization
management, financial planning, products evaluation and recommendation. Rational …

If we want people to trust AI systems, we need to provide the systems we create with the
ability to discriminate between what humans would consider good and bad decisions. The …

Conditional preference networks (CP-nets) have recently emerged as a popular language
capable of representing ordinal preference relations in a compact and structured manner. In …

While there are several languages for representing combinatorial preferences over sets of
alternatives, none of these are well-suited to the representation of ordinal preferences over …