We discuss models of updating that depart from Bayes' rule even when it is well-defined.
After reviewing Bayes' rule and its foundations, we begin our analysis with models of non …

The Bayesian model has been used in psychology as the standard reference for the study of
probability revision. In the first part of this paper we show that this traditional choice restricts …

We introduce and characterize inertial updating of beliefs. Under inertial updating, a
decision maker (DM) chooses a belief that minimizes the subjective distance between their …

In this Book we argue that the fruitful interaction of computer vision and belief calculus is
capable of stimulating significant advances in both fields. From a methodological point of …

In this paper, we solve the problem of approximating a belief measure with a necessity
measure or “consonant belief function” in a geometric framework. Consonant belief functions …

We study belief revision when information is given as a set of relevant probability
distributions. This flexible setting encompasses (i) the standard notion of information as an …

I propose an axiomatic framework for belief revision when new information is qualitative, of
the form “event A is at least as likely as event B.” My decision maker need not have beliefs …

We interpret the problem of updating beliefs as a choice problem (selecting a posterior from
a set of admissible posteriors) with a reference point (prior). We use AGM belief revision to …

In this paper we study the problem of conditioning a belief function b with respect to an event
A by geometrically projecting such belief function onto the simplex associated with A in the …

Uncertainty is of paramount importance in artificial intelligence, applied science, and many
other areas of human endeavour. Whilst each and every one of us possesses some intuitive …