When a new piece of information contradicts a currently held belief, one has to modify the set of beliefs in order to restore its consistency. In the case where it is necessary to give up a belief, some of them are less likely to be abandoned than others. The concept of epistemic entrenchment is used by some AI approaches to explain this fact based on formal properties of the belief set (e. g. ...

We study learning curves for Gaussian process regression which characterise performance in terms of the Bayes error averaged over datasets of a given size. Whilst learning curves are in general very difficult to calculate we show that for discrete input domains, where similarity between input points is characterised in terms of a graph, accurate predictions can be obtained. These should in fact...

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I Introduction What is the epistemic significance of discovering that one of your beliefs depends on an irrelevant causal factor? Suppose that you have a relatively high degree of belief in some proposition. Suppose that you then come to learn that your belief was (in part) caused by an irrelevant factor, a factor that does not bear on the truth of the proposition or on your possession of evide...

We propose a formal framework to support belief revision based on a cognitive model of credibility and trust. In this framework, the acceptance of information coming from a source depends on (i) the agent’s goals and beliefs about the source’s goals, (ii) the credibility, for the agent, of incoming information, and (iii) the agent’s beliefs about the context in which it operates. This makes it ...

We propose a measure of the degree of ambiguity associated with a belief function and a nonparametric method to estimate it. The degree of ambiguity associated with a belief function is measured by the Kullback-Leibler diameter of the set of probability measures compatible with it. It is shown that an estimator based on the empirical version of the unambiguous measure generating the belief func...

The study of alternative combination rules in DS theory when evidence is in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. These studies have mainly focused on investigating which alternative would be appropriate for which conflicting situation, under the assumption that a conflict is identified. The issue of detection (or identi...