On the implication problem for probabilistic conditional independency
نویسندگان
چکیده
منابع مشابه
On the implication problem for probabilistic conditional independency
The implication problem is to test whether a given set of independencies logically implies another independency. This problem is crucial in the design of a probabilistic reasoning system. We advocate that Bayesian networks are a generalization of standard relational databases. On the contrary, it has been suggested that Bayesian networks are different from the relational databases because the i...
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A lattice-theoretic framework is introduced that permits the study of the conditional independence (CI) implication problem relative to the class of discrete probability measures. Semi-lattices are associated with CI statements and a finite, sound and complete inference system relative to semi-lattice inclusions is presented. This system is shown to be (1) sound and complete for saturated CI st...
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It has been suggested that Bayesian networks and relational databases are different because the implication problems for probabilistic conditional independence and embedded multivalued dependency do not always coincide. The present study indicates that the implication problems coincide on solvable classes of dependencies and differ on unsolvable classes. We therefore maintain that Bayesian netw...
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Bayesian networks serve as the basis for developing probabilistic expert systems and have been applied widely in artificial intelligence. Previous research has argued that Bayesian networks and relational databases are different by showing that the logical implication of conditional independence (CI) and embedded multivalued dependency (EMVD) do not always coincide. In this paper, we show that ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
سال: 2000
ISSN: 1083-4427
DOI: 10.1109/3468.895901