2U an exact interval propagation algorithm for polytrees with binary variables. - Fagiuoli, Enrico (Artificial intelligence.)
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 previous termexactnext term algorithmic solutions. An previous termexact propagation algorithmnext term for the updating of a previous termpolytree with binary variablesnext term is derived. The overall complexity is linear to the size of the network, when the maximum number of parents is fixed.