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
The use of aggregation in causal simulation
Artificial Intelligence
The limits of qualitative simulation
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Taming intractible branching in qualitative simulation
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
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Qualitative simulation faces an intrinsic problem of scale: the number of limit hypotheses grows exponentially with the number of parameters approaching limits. We present a method called Time-Scale Abstraction for structuring a complex system as a hierarchy of smaller, interacting equilibrium mechanisms. Within this hierarchy, a given mechanism views a slower one as being constant, and a faster one as being instantaneous. A perturbation to a fast mechanism may be seen by a slower mechanism as a displacement of a monotonic function constraint. We demonstrate the time-scale abstraction hierarchy using the interaction between the water and sodium balance mechanisms in medical physiology, an example drawn from a larger, fully implemented, program. Where the structure of a large system permits decomposition by time-scale, this abstraction method permits qualitative simulation of otherwise intractibly complex systems.