Call for Papers

Many problems in AI (in reasoning, planning, learning, perception and robotics) require the agent to operate with incomplete or uncertain information. The objective of this track is to present and discuss a broad and diverse range of current work on uncertain reasoning, including theoretical and applied research based on different paradigms. We hope that the variety and richness of this track will help to promote cross fertilization among the different approaches for uncertain reasoning, and in this way foster the development of new ideas and paradigms.

The Special Track on Uncertain Reasoning (UR) is the oldest track in FLAIRS conferences, running annually since 1996. The UR 2023 Special Track at the 37th International Florida Artificial Intelligence Research Society Conference (FLAIRS-37) is the 29th in the series. Like the past tracks, UR'24 seeks to bring together researchers working on broad issues related to reasoning under uncertainty.

Papers on all aspects of uncertain reasoning are invited. Papers of particular interest include, but are not limited to:

• Uncertain reasoning formalisms, calculi and methodologies
• Reasoning with probability, possibility, fuzzy logic, belief function, vagueness, granularity, rough sets, and probability logics
• Modeling and reasoning using imprecise and indeterminate information, such as: Choquet capacities, comparative orderings, convex sets of measures, and interval-valued probabilities
• Exact, approximate and qualitative uncertain reasoning
• Probabilistic graphical models of uncertainty such as: Bayesian networks, Markov random field, probabilistic circuits
• Multi-agent uncertain reasoning and decision-making
• Decision-theoretic planning and Markov decision process
• Temporal reasoning and uncertainty
• Non-monotonic reasoning
• Conditional Logics
• Argumentation theory
• Belief change and merging
• Similarity-based reasoning
• Ontologies and description logics
• Construction of models from elicitation, data mining and knowledge discovery
• Uncertain reasoning in information retrieval, filtering, fusion, diagnosis, prediction, situation assessment
• Uncertain reasoning in data management
• Practical applications of uncertain reasoning
• Learning probabilistic models
• Applications in computer vision and animation

Program Committee

Track Chairs

• Tanya Braun (University of Münster)
• Kai Sauerwald (University of Hagen)

PC Members

• Alessandro Antonucci (IDSIA, Switzerland)
• Ofer Arieli (The Academic College of Tel-Aviv, Israel)
• Christoph Beierle (FernUniversität in Hagen, Germany)
• Salem Benferhat (University of Artois, France)
• Nizar Bouguila (Concordia University, Canada)
• Lluís Godo (University of Barcelona, Spain)
• Christophe Gonzales (LIS, France)
• Gabriele Kern-Isberner (University of Technology Dortmund, Germany)
• Vladik Kreinovich (University of Texas at El Paso, US)
• Nicholas Mattei (Tulane University, US)
• Tommie Meyer (University of Cape Town, South Africa)
• Arthur Paul Pedersen (The City College of New York, US)
• Rafael Peñaloza Nyssen (University of Milano-Bicocca, Italy)
• Carlo Taticchi (Università degli Studi di Perugia, Italy)
• Choh Man Teng (Institute for Human and Machine Cognition, US)

Other Information

FLAIRS 37 will be held at the Hilton Sandestin Beach Golf Resort and Spa, in Miramar Beach, Florida, USA. Additional information on the conference location and travel planning can be found here. Feel free to write the organizers (tanya.braun@uni-muenster.de or kai.sauerwald@fernuni-hagen.de) for any further information about the special track.