QR 2015 - 28th International Workshop on Qualitative Reasoning

We build qualitative models to predict and understand our world from incomplete, imprecise, or uncertain data. Our qualitative models span natural systems (physics, biology, ecology, geology), social systems (economics, cultural decision-making), cognitive systems (conceptual learning, spatial reasoning, intelligent tutors, robotics), and more.
The qualitative reasoning (QR) community includes researchers in Artificial Intelligence, Engineering, Cognitive Science, and Natural Sciences, commonly seeking to understand, develop, and exploit the ability to reason qualitatively. This broadly includes:
Developing new formalisms and algorithms for general qualitative reasoning.
Building and evaluating predictive, prescriptive, diagnostic, or explanatory qualitative models in novel domains.
Characterizing how humans learn and reason qualitatively about the world with incomplete knowledge.
Developing novel, formal representations to describe central aspects of our world: time, space, change, uncertainty, causality, and continuity.
The International Workshop on Qualitative Reasoning provides a forum for researchers from multiple perspectives to share research progress toward these goals. The workshop will be held at the Minneapolis, MN campus of the University of St. Thomas and at SIFT, August 10-12, 2015, in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI).
Topics:
Qualitative knowledge representation & reasoning (KR&R) in physical, biological and social sciences.
Qualitative KR&R for mitigating uncertainty, incompleteness, or imprecision.
Integrating qualitative methods with quantitative, statistical methods and other formalisms.
Qualitative KR&R for diagnosis, design, and monitoring of physical systems.
Applications of qualitative reasoning, including education, science, and engineering.
Cognitive models using qualitative KR&R.
Qualitative reasoning in understanding language, sketches, images, and other kinds of signals and data sources.
Formalization, axiomatization, and mathematical foundations of qualitative reasoning.