A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Commonsense reasoning about causality: deriving behavior from structure
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative analysis of MOS circuits
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Combining discrete and continuous process models
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
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Intuitively, discontinuous changes can be seen as very rapid continuous changes. A couple of alternative methods based on this ontology are presented and compared. One, called the approximation method, approximates discontinuous change by continuous function and then calculates a limit. The other, called the direct method, directly creates a chain of hypothetical intermediate states (mythical instants) which a given circuit is supposed to go through during a discontinuous change. Although the direct method may fail to predict certain properties of discontinuity and its applicability is limited, it is more efficient than the approximation method. The direct method has been fully implemented and incorporated into an existing qualitative reasoning program.