Representations of commonsense knowledge
Representations of commonsense knowledge
A qualitative physics based on confluences
Readings in qualitative reasoning about physical systems
Combining logic and differential equations for describing real-world systems
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Qualitative reasoning about fluids and mechanics
Qualitative reasoning about fluids and mechanics
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Describing Rigid Body Motions in a Qualitative Theory of Spatial Regions
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An attempt to formalise a non-trivial benchmark problem in common sense reasoning
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Processes and continuous change in a SAT-based planner
Artificial Intelligence
Continuous Shape Transformation and Metrics on Regions
Fundamenta Informaticae - Qualitative Spatial Reasoning
Multiples representations of knowledge in a mechanics problem-solver
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 1
Reasoning about fluids via molecular collections
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
How does a box work? A study in the qualitative dynamics of solid objects
Artificial Intelligence
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This paper presents a theory that supports commonsense, qualitative reasoning about the flow of liquid around slowly moving solid objects; specifically, inferring that liquid can be poured from one container to another, given only qualitative information about the shapes and motions of the containers. It shows how the theory and the problem specification can be expressed in a first-order language; and demonstrates that this inference and other similar inferences can be justified as deductive conclusions from the theory and the problem specification.