We revisit the problem of revising probabilistic beliefs using uncertain evidence, and report results on four major issues relating to this problem: How to specify uncertain evide...
Belief revision performs belief change on an agent's beliefs when new evidence (either of the form of a propositional formula or of the form of a total pre-order on a set of ...
Intelligent agents require methods to revise their epistemic state as they acquire new information. Jeffrey’s rule, which extends conditioning to uncertain inputs, is used to re...
Salem Benferhat, Didier Dubois, Henri Prade, Mary-...
This paper reports our investigation on the problem of belief update in Bayesian networks (BN) using uncertain evidence. We focus on two types of uncertain evidences, virtual evid...
Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...