Elsevier

Artificial Intelligence

Volume 106, Issue 1, November 1998, Pages 77-107
Artificial Intelligence

2U: an exact interval propagation algorithm for polytrees with binary variables

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Abstract

This paper addresses the problem of computing posterior probabilities in a discrete Bayesian network where the conditional distributions of the model belong to convex sets. The computation on a general Bayesian network with convex sets of conditional distributions is formalized as a global optimization problem. It is shown that such a problem can be reduced to a combinatorial problem, suitable to exact algorithmic solutions. An exact propagation algorithm for the updating of a polytree with binary variables is derived. The overall complexity is linear to the size of the network, when the maximum number of parents is fixed.

Keywords

Bayesian networks
Convex sets
Credal sets
Intervals
Uncertain reasoning
Inference

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