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
Qualitative analysis of MOS circuits
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
The use of aggregation in causal simulation
Artificial Intelligence
Self-explanatory simulations: an integration of qualitative and quantitative knowledge
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
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A general problem in qualitative physics is determining the consequences of assumptions about the behavior of a system. If the space of behaviors is represented by an envisionment, many such consequences can be represented by pruning states from the envisionment. This paper provides a formal logic of occurrence which justifies the algorithms involved and provides a language for relating specific histories to envision ments The concepts and axioms are general enough to be applicable to any system of qualitative physics. We further propose the concept of transverse quantities as a general solution to qualitative versions of Zeno's paradox. The utility of these ideas is illustrated by a rational reconstruction of the pruning algorithms used in FROB, a working AI program.