This paper presents new methods for probabilistic belief revision and information fusion. By making use of the principles of optimum entropy (ME-principles), we define a generali...
Abstract. In this paper, we present a revision strategy of revising a conditional probabilistic logic program (PLP) when new information is received (which is in the form of probab...
Belief revision theory aims to describe how one should change one's beliefs when they are contradicted by newly input information. The guiding principle of belief revision th...
We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability...
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-...