Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic evaluation of counterfactual queries
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
A new characterization of the experimental implications of causal Bayesian networks
Eighteenth national conference on Artificial intelligence
Journal of Artificial Intelligence Research
Decision-theoretic foundations for causal reasoning
Journal of Artificial Intelligence Research
Developing social networks for artificial societies from survey data
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
Local characterizations of causal bayesian networks
GKR'11 Proceedings of the Second international conference on Graph Structures for Knowledge Representation and Reasoning
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We offer a complete characterization of the set of distributions that could be induced by local interventions on variables governed by a causal Bayesian network of unknown structure, in which some of the variables remain unmeasured. We show that such distributions are constrained by a simply formulated set of inequalities, from which bounds can be derived on causal effects that are not directly measured in randomized experiments.