Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Revision rules for convex sets of probabilities
Mathematical models for handling partial knowledge in artificial intelligence
2U: an exact interval propagation algorithm for polytrees with binary variables
Artificial Intelligence
Artificial Intelligence
Expert Systems and Probabiistic Network Models
Expert Systems and Probabiistic Network Models
Semigraphoids and structures of probabilistic conditional independence
Annals of Mathematics and Artificial Intelligence
Probability Intervals Over Influence Diagrams
IEEE Transactions on Pattern Analysis and Machine Intelligence
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Separation Properties of Sets of Probability Measures
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Axioms for probability and belief-function proagation
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Irrelevance and independence relations in Quasi-Bayesian networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Independence concepts for convex sets of probabilities
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Robustness analysis of Bayesian networks with local convex sets of distributions
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Updating beliefs with incomplete observations
Artificial Intelligence
Epistemic irrelevance on sets of desirable gambles
Annals of Mathematics and Artificial Intelligence
Computing lower and upper expectations under epistemic independence
International Journal of Approximate Reasoning
Hill-climbing and branch-and-bound algorithms for exact and approximate inference in credal networks
International Journal of Approximate Reasoning
ACM Transactions on Computational Logic (TOCL)
International Journal of Approximate Reasoning
Artificial Intelligence
Conditional independence structure and its closure: Inferential rules and algorithms
International Journal of Approximate Reasoning
Graphical models for imprecise probabilities
International Journal of Approximate Reasoning
Acyclic directed graphs representing independence models
International Journal of Approximate Reasoning
Compositional models and conditional independence in evidence theory
International Journal of Approximate Reasoning
Inference with separately specified sets of probabilities in credal networks
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
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This paper investigates the concept of strong conditional independence for sets of probability measures. Couso, Moral and Walley [7] have studied different possible definitions for unconditional independence in imprecise probabilities. Two of them were considered as more relevant: epistemic independence and strong independence. In this paper, we show that strong independence can have several extensions to the case in which a conditioning to the value of additional variables is considered. We will introduce simple examples in order to make clear their differences. We also give a characterization of strong independence and study the verification of semigraphoid axioms.