A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks. Copyright © 2007 by SIPTA.
|Original language||American English|
|Number of pages||10|
|State||Published - 1 Dec 2007|
|Event||ISIPTA 2007 - Proceedings of the 5th International Symposium on Imprecise Probability: Theories and Applications - |
Duration: 1 Dec 2007 → …
|Conference||ISIPTA 2007 - Proceedings of the 5th International Symposium on Imprecise Probability: Theories and Applications|
|Period||1/12/07 → …|