Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Computer aided kinematics and dynamics of mechanical systems. Vol. 1: basic methods
Computer aided kinematics and dynamics of mechanical systems. Vol. 1: basic methods
Automatic qualitative analysis of dynamic systems using piecewise linear approximations
Artificial Intelligence
Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Understanding complex dynamics by visual and symbolic reasoning
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Modeling and Simulation in Chemical Engineering
Modeling and Simulation in Chemical Engineering
The Dynamicist''s Workbench: I ---Automatic Preparation of Numerical Experiments
The Dynamicist''s Workbench: I ---Automatic Preparation of Numerical Experiments
Taming intractible branching in qualitative simulation
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Extracting and representing qualitative behaviors of complex systems in phase spaces
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Scaling up self-explanatory simulators polynomial time compilation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Using modeling knowledge to guide design space search
Artificial Intelligence
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Qualitative reasoners have been hamstrung by the inability to analyze large models. This includes self-explanatory simulators, which tightly integrate qualitative and numerical models to provide both precision and explanatory power. While they have important potential applications in training, instruction, and conceptual design, a critical step towards realizing this potential is the ability to build simulators for medium-sized systems (i.e., on the order of ten to twenty independent parameters). This paper describes a new method for developing self-explanatory simulators which scales up. While our method involves qualitative analysis, it does not rely on envisioning or any other form of qualitative simulation. We describe the results of an implemented system which uses this method, and analyze its limitations and potential.