Graph algorithms and NP-completeness
Graph algorithms and NP-completeness
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The qualitative process engine
Readings in qualitative reasoning about physical systems
Maintaining knowledge about temporal intervals
Communications of the ACM
A Study of Qualitative and Geometric Knowledge in Reasoning about Motion
A Study of Qualitative and Geometric Knowledge in Reasoning about Motion
Stochastic analysis of qualitative dynamics
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
KNOWLEDGE-BASED VALIDATION FOR HYDROLOGICAL INFORMATION SYSTEMS
Applied Artificial Intelligence
Model-based diagnosis with qualitative temporal uncertainty
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Physiological applications of consistency-based diagnosis
Artificial Intelligence in Medicine
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Incrementally maintaining a qualitative understanding of physical system behavior based on observations is crucial to real-time process monitoring, diagnosis, and control. This paper describes the DATMI theory for dynamically maintaining a pinterp-space, a concise representation of the local and global interpretations consistent with observations over time. Each interpretation signifies an alternative path of states in a qualitative envisionment. DATMI can use domain-specific knowledge about state and transition probabilities to maintain the best working interpretation. By maintaining the space of alternative interpretations as well, DATMI avoids the need for extensive backtracking to handle incomplete or faulty data.