Idea and Motivation
The notion of “preference” has a long tradition in various scientific disciplines, including economics and the social sciences, operations research and the decision sciences, psychology, and philosophy. Over the past decades, it has also been studied intensively in artificial intelligence (AI), where preferences provide a means for specifying desires in a declarative and intelligible way, a point of critical importance for effective knowledge representation and reasoning. Moreover, recommender systems often aim to learn user preferences to provide better recommendations. And, recently, alignment methods aim to improve Large Language Models to generate output that is closer to human preference. This workshop brings together researchers from different disciplines interested in preferences. The goal is to stimulate the interaction between these disciplines, to deepen the understanding of preferences and explore new perspectives, and thereby to advance the state of the art of preferences in AI.
Speakers
- Arduin Findeis (Cambridge)
- Johannes Fürnkranz (JKU Linz)
- Jobst Heitzig (Potsdam Institute for Climate Impact Research)
- Dominik Klein (Utrecht)
- Christian List (LMU/MCMP)
- Silvia Milano (Exeter)
- Ignacio Ojea Quintana (LMU/MCMP)
- Julian Rodemann (LMU)
- Zoi Terzopoulou (GATE, Jean Monnet University)
- Paolo Viappiani (Paris Sorbonne)
Program and registration
Program
TBA
Abstracts
TBA
Organizers
Registration
Attendance is free but registration is required by sending an email to Office.Leitgeb@lrz.uni-muenchen.de.
Venue
ZEPP Library, LMU main building, room M210, Geschwister-Scholl-Platz 1, 80539 Munich