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MICAI
2005
Springer

Directed Cycles in Bayesian Belief Networks: Probabilistic Semantics and Consistency Checking Complexity

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Directed Cycles in Bayesian Belief Networks: Probabilistic Semantics and Consistency Checking Complexity
Although undirected cycles in directed graphs of Bayesian belief networks have been thoroughly studied, little attention has so far been given to a systematic analysis of directed (feedback) cycles. In this paper we propose a way of looking at those cycles; namely, we suggest that a feedback cycle represents a family of probabilistic distributions rather than a single distribution (as a regular Bayesian belief network does). A non-empty family of distributions can be explicitly represented by an ideal of conjunctions with interval estimates on the probabilities of its elements. This ideal can serve as a probabilistic model of an experts uncertain knowledge pattern; such models are studied in the theory of algebraic Bayesian networks. The family of probabilistic distributions may also be empty; in this case, the probabilistic assignment over cycle nodes is inconsistent. We propose a simple way of explicating the probabilistic relationships an isolated directed cycle contains, give an al...
Alexander L. Tulupyev, Sergey I. Nikolenko
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where MICAI
Authors Alexander L. Tulupyev, Sergey I. Nikolenko
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