[QR2025 - FINAL CALL FOR PAPERS]

The Qualitative Reasoning (QR) community develops qualitative representations and reasoning algorithms to understand the world from incomplete, imprecise, or uncertain data. Our qualitative models span natural systems (e.g., physics, biology, ecology, geology), social systems (e.g., economics, cultural decision-making), cognitive systems (e.g., conceptual learning, spatial reasoning, intelligent tutors, robotics), and more. The International Workshop on QR provides a forum for researchers from multiple perspectives to share research progress toward these goals. The workshop will be held at IJCAI 2025, Montreal.

The QR community includes researchers in Artificial Intelligence, Engineering, Cognitive Science, Applied Mathematics, and Natural Sciences, commonly seeking to understand, develop, and exploit the ability to reason qualitatively. This broadly includes:

- Developing new formalisms and algorithms for qualitative reasoning
- Building and evaluating predictive, prescriptive, diagnostic, or explanatory qualitative models in novel domains.
- Characterizing how humans learn and reason qualitatively about the (physical) world with incomplete knowledge
- Developing novel, formal representations to describe central aspects of our world: time, space, change, uncertainty, causality, and continuity








[TOPICS INCLUDE]

- Qualitative modeling in physical, biological and social sciences, and in engineering.
- QR to capture common sense reasoning.
- Methods that integrate QR with other forms of knowledge representation, including quantitative methods.
- Integration of QR and machine learning, for example learning qualitative representations or improve machine learning by means of QR.
- Using QR for diagnosis, design, and monitoring of physical systems.
- Applications of QR, including education, science, and engineering.
- Cognitive models of QR, including the use of existing QR formalisms for cognitive modeling and results from other areas of cognitive science for qualitative reasoning.
- Using QR in understanding language, decision-making, sketches, images, and other kinds of signals and data sources.
- Formalization, axiomatization, and mathematical foundations of QR.








[SUBMISSION]

We invite the following types of submissions:

- Technical papers (full/short) – novel research, including late-breaking ideas
- Summary papers – highlight existing work relevant to QR
- Application/demo papers – real-world applications, software, and implementations

Format: Full (7 pages), Short (3 pages), +1 page for references – IJCAI format Review Process: Peer-reviewed (at least 2 reviewers per paper) Proceedings: Working papers collection

Accepted papers will be published as a collection of working papers. As QR 2025 is a workshop, not a conference, submission of the same paper to conferences (e.g. AAAI, ECAI, or IJCAI) or journals is acceptable, but must be indicated. To accommodate the publishing traditions of different fields, authors of accepted papers can ask that only a one-page abstract of their paper appear in the proceedings. The workshop is also open to people who would like to attend without submitting a paper.








[PROGRAM CHAIR]

Kenneth D. Forbus, Northwestern University, forbus@northwestern.edu
Marco Kragten, Amsterdam University of Applied Sciences, m.kragten@hva.nl
Moritz Bayerkuhnlein, University of Lübeck, moritz.bayerkuhnlein@uni-luebeck.de