Probabilistic reasoning in decision support systems: from computation to common sense
Probabilistic reasoning in decision support systems: from computation to common sense
Artificial Intelligence
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Caveats for Causal Reasoning with Equilibrium Models
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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The term "changes in structure," originating from work in econometrics, refers to structural modifications invoked by actions on a causal model. In this paper we formalize the representation of reversibility of a mechanism in order to support modeling of changes in structure in systems that contain reversible mechanisms. Causal models built on our formalization can answer two new types of queries: (1) When manipulating a causal model (i.e., making an endogenous variable exogenous), which mechanisms are possibly invalidated and can be removed from the model? (2) Which variables may be manipulated in order to invalidate and, effectively, remove a mechanism from a model?.