Planning for conjunctive goals
Artificial Intelligence
Nonmonotonic logic and temporal projection
Artificial Intelligence
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Representing and reasoning with probabilistic knowledge: a logical approach to probabilities
Qualitative spatial reasoning: the CLOCK project
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Automated reasoning about machines
Artificial Intelligence
Qualitative rigid-body mechanics
Artificial Intelligence
Rigid-Body Dynamics with Friction and Impact
SIAM Review
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Statistical Language Learning
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
A First-order Theory of Communication and Multi-agent Plans
Journal of Logic and Computation
Multiples representations of knowledge in a mechanics problem-solver
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 1
Qualitative kinematics in mechanisms
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Formal theories of action (preliminary report)
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Pouring liquids: A study in commonsense physical reasoning
Artificial Intelligence
Artificial Intelligence
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This paper is an in-depth study of qualitative physical reasoning about one particular scenario: using a box to carry a collection of objects from one place to another. Specifically we consider the plan, plan1 ''Load objects uCargo into box oBox one by one; carry oBox from location l1 to location l2''. We present qualitative constraints on the shape, starting position, and material properties of uCargo and oBox and on the characteristics of the motion that suffice to make it virtually certain that plan1 can be successfully executed. We develop a theory, consisting mostly of first-order statements together with two default rules, that supports an inference of the form ''If conditions XYZ hold, and the agent attempts to carry out plan1 then presumably he will succeed''. Our theory is elaboration tolerant in the sense that carrying out the analogous inference for carrying objects in boxes with lids, in boxes with small holes, or on trays can reuse much of the same knowledge. The theory integrates reasoning about continuous time, Euclidean space, commonsense dynamics of solid objects, and semantics of partially specified plans.