Evaluating the Uncertainty of a Boolean Formula with Belief Functions

Christelle Jacob (1, 2) , Didier Dubois (1, 3) , Janette Cardoso (2)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 DMIA - Département de Mathématiques, Informatique, Automatique
3 QUB - Queen's University [Belfast]

In fault-tree analysis, probabilities of failure of components are often assumed to be precise and the events are assumed to be independent, but this is not always verified in practice. By giving up some of these assumptions, results can still be computed, even though it may require more expensive algorithms, or provide more imprecise results. Once compared to those obtained with the simplified model, the impact of these assumptions can be evaluated. This paper investigates the case when probability intervals of atomic propositions come from independent sources of information. In this case, the problem is solved by means of belief functions. We provide the general framework, discuss computation methods, and compare this setting with other approaches to evaluating the uncertainty of formulas.

Mots clés: Fault-trees; Belief functions; Boolean satisfaction

Domaines: Intelligence artificielle [cs.AI]; Algorithme et structure de données [cs.DS]

Christelle Jacob, Didier Dubois, Janette Cardoso. Evaluating the Uncertainty of a Boolean Formula with Belief Functions. 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU 2012), Jul 2012, Catane, Italy. pp.521-531, ⟨10.1007/978-3-642-31718-7_54⟩. ⟨hal-03413952⟩