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
Knowledge Acquisition
A model-based consultation system for the long-term management of glaucoma
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
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We describe a Functional Modeling approach for understanding biological systems and using that understanding for consequence finding. In our Functional Approach, abstractly stated system goals (functions) are used to organize (index) causal understanding about the system. A functional representationm of a system then provides the framework for performing a type of qualitative reasoning aimed at determining consequences on the system given particular boundary conditions. As an example of a complex biological system, we exhibit our initial results in applying our approach to an ecological problem, modeling the West-African nitrogen cycle. We show that our approach provides leverage for handling the complexity, uncertainty and incomplete knowledge inherent in the domain.