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.
|Title of host publication||International Symposium on Imprecise Probability: Theories and Applications (ISIPTA)|
|Number of pages||10|
|Publication status||Published - 2007|
Bibliographical note(oral presentation, blind peer reviewed by >3 reviewers)
de Campos, C. P., & Cozman, F. G. (2007). Inference in Credal Networks Through Integer Programming. In International Symposium on Imprecise Probability: Theories and Applications (ISIPTA) (pp. 145-154). SIPTA. http://www.eeecs.qub.ac.uk/~c.decampos/publist/papers/decampos2007b.pdf