Andrés Cano Utrera , Manuel Gómez Olmedo , Serafín Moral Callejón , Joaquín Abellán Mulero
This paper proposes two new algorithms for inference in credal networks. These algorithms enable probability intervals to be obtained for the states of a given query variable. The first algorithm is approximate and uses the hill-climbing technique in the Shenoy¿Shafer architecture to propagate in join trees; the second is exact and is a modification of Rocha and Cozman¿s branch-and-bound algorithm, but applied to general directed acyclic graphs
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