Computing with generalized p-boxes: preliminary results
Résumé
The need to propagate uncertainties through a model is present in many applications. In most cases, the nature of this model is either graphical or functional. In this paper, we interest ourselves to the latter case. We consider here that uncertainty on each model input is described either by generalized p-boxes or possibility distributions, two special cases of random sets that can be interpreted in term of condence bounds over nested sets. We then study their practical propagation for different cases.
Domaines
Intelligence artificielle [cs.AI]
Origine : Fichiers produits par l'(les) auteur(s)