A theory of diagnosis from first principles
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Constraint propagation algorithms for temporal reasoning: a revised report
Readings in qualitative reasoning about physical systems
Exact and approximate reasoning about temporal relations
Computational Intelligence
A spectrum of logical definitions of model-based diagnosis
Computational Intelligence
Readings in model-based diagnosis
Readings in model-based diagnosis
Characterizing diagnoses and systems
Artificial Intelligence
Complexity and algorithms for reasoning about time: a graph-theoretic approach
Journal of the ACM (JACM)
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Reasoning about temporal relations: a maximal tractable subclass of Allen's interval algebra
Journal of the ACM (JACM)
Maintaining knowledge about temporal intervals
Communications of the ACM
Diagnostic Problem Solving: Combining Heuristic, Approximate and Casual Reasoning
Diagnostic Problem Solving: Combining Heuristic, Approximate and Casual Reasoning
Temporal Logic Based on Characteristic Functions
KI '95 Proceedings of the 19th Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
SIDIA: Extending Prediction Based Diagnosis to Dynamic Models
Proceedings of the International Workshop on Expert Systems in Engineering, Principles and Applications
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Generating causal networks for mobile multi-agent systems with qualitative regions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Compilation for critically constrained knowledge bases
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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The paper is devoted topresentation of the idea of Temporal Causal Networks (TCN).Temporal Causal Networks constitute a tool for representing anddealing with causal dependencies propagation over time. A temporalcausal network is a causal network incorporating explicit representationof time during which its symptoms/nodes are valid, not valid,or unknown. The atemporal causal structure is basically an AND/OR/NOTcausal graph, i.e. a causal graph incorporating basic logical connectivesfor the representation of different types of causal dependencies. Thepresented approach uses a specific time constraints propagationalgorithm to determine possible system behavior in time. Themain application includes simulation, monitoring and elementsof diagnostic reasoning for dynamic systems with explicit timerepresentation.