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.
Keywords. Credal network, probability intervals, Bayesian networks, strong independence, hill-climbing and branch-and-bound algorithms.
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Authors addresses:
Andrés Cano
Dpto. Ciencias de la Computaci�n e I.A.
ETS Ingenier�a Inform�tica
Avda. Andalucia s/n
Granada 18071
Spain
Manuel Gómez
Dpto. Ciencias de la Computación e I.A.
E.T.S. Ingeniería Informática
C// Periodista Daniel Saucedo Aranda
18071 Granada
Serafín Moral
Dpto. Ciencias de la Computación e IA
ETSI Informática
Universidad de Granada
18071 Granada - Spain
E-mail addresses:
| Andrés Cano | acu@decsai.ugr.es |
| Manuel Gómez | mgomez@decsai.ugr.es |
| Serafín Moral | smc@decsai.ugr.es |
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