On the Desirability of Acyclic Database Schemes
Journal of the ACM (JACM)
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
On Stochastic Conditional Independence: the Problems of Characterization and Description
Annals of Mathematics and Artificial Intelligence
Heuristic Algorithms for the Triangulation of Graphs
IPMU'94 Selected papers from the 5th International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems, Advances in Intelligent Computing
Formal Properties of Conditional Independence in Different Calculi of AI
ECSQARU '93 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Axioms for probability and belief-function proagation
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Compositional models and conditional independence in evidence theory
International Journal of Approximate Reasoning
Composition of probability measures on finite spaces
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
International Journal of Approximate Reasoning
Compositional models in valuation-based systems
International Journal of Approximate Reasoning
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When applying any technique of multidimensional models to problems of practice, one always has to cope with two problems: the necessity to represent the models with a ''reasonable'' number of parameters and to have sufficiently efficient computational procedures at one's disposal. When considering graphical Markov models in probability theory, both of these conditions are fulfilled; various computational procedures for decomposable models are based on the ideas of local computations, whose theoretical foundations were laid by Lauritzen and Spiegelhalter. The presented contribution studies a possibility of transferring these ideas from probability theory into Dempster-Shafer theory of evidence. The paper recalls decomposable models, discusses connection of the model structure with the corresponding system of conditional independence relations, and shows that under special additional conditions, one can locally compute specific basic assignments which can be considered to be conditional.