Publications
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Credal networks under epistemic irrelevance using sets of desirable gambles Ghent University
We present a new approach to credal networks, which are graphical models that generalise Bayesian nets to deal with imprecise probabilities. Instead of applying the commonly used notion of strong independence, we replace it by the weaker notion of epistemic irrelevance. We show how assessments of epistemic irrelevance allow us to construct a global model out of given local uncertainty models, leading to an intuitive expression for the so-called ...
Credal networks under epistemic irrelevance : the sets of desirable gambles approach Ghent University
Reintroducing credal networks under epistemic irrelevance Ghent University
Epistemic irrelevance in credal networks : the case of imprecise Markov trees Ghent University
We replace strong independence in credal networks with the weaker notion of epistemic irrelevance. Focusing on directed trees, we show how to combine local credal sets into a global model, and we use this to construct and justify an exact message-passing algorithm that computes updated beliefs for a variable in the tree. The algorithm, which is essentially linear in the number of nodes, is formulated entirely in terms of coherent lower ...
Allowing for probability zero in credal networks under epistemic irrelevance Ghent University
We generalise CozmanU+2019s concept of a credal network under epistemic irrelevance (2000) to the case where lower (and upper) probabilities are allowed to be zero. Our main definition is expressed in terms of coherent lower previsions and imposes epistemic irrelevance by means of strong coherence rather than element-wise BayesU+2019s rule. We also present a number of alternative representations for the resulting joint model, both in terms of ...