There has been an ever-increasing interest in multi-disciplinary research on representing and reasoning with imperfect data. Possibilistic networks present one of the powerful frameworks of interest for representing uncertain and imprecise information. This paper covers the problem of their parameters learning from imprecise datasets, i.e., containing multi-valued data. We propose in the first ...

Dempster Shafer theory of evidence (DS theory) and possibility theory are two main formalisms in modelling and reasoning with uncertain information. These two theories are inter-related as already observed and discussed in many papers (e.g. [DP82,DP88b]). One aspect that is common to the two theories is how to quantitatively measure the degree of conflict (or inconsistency) between pieces of un...

Uncertainty importance measures typically reflect the degree to which uncertainty about risk and reliability parameters at the component level influences uncertainty about parameters at the system level. The definition of these measures is typically founded on a Bayesian perspective where subjective probabilities are used to express epistemic uncertainty; hence, they do not reflect the effect o...

When merging belief functions, Dempster rule of combination is justified only when sources can be considered as independent. When dependencies are ill-known, it is usual to ask the merging operation to satisfy the property of idempotence, as this property ensures a cautious behaviour in the face of dependent sources. There are different strategies to find such rules for belief functions. One st...

The charter of SRC i s t o a d v ance both the state of knowledge and the state of the art in computer systems. From our establishment in 1984, we have performed basic and applied research to support Digital's business objectives. Our current work includes exploring distributed personal computing on multiple platforms, networking, programming technology, system modelling and management techniqu...

We overview the existing conditional independence concepts from the viewpoint of their relation to possibility theory. We will show that a suitable notion — from this perspective — seems to be strong independence in the wider framework of credal sets.

Possibility is considered as a promising mathematical tool to represent that particular case of incomplete information given by a measurement result. A measurement result can be affected by systematic and random effects. The combination of random contributions in the possibility theory returns only approximated results, and it is important to identify an optimal combination method to obtain acc...

This paper is about the relation between contrast and ‘prominent positions’ − i.e. onsets, stressed syllables, and root-initial syllables.1 A number of works have assumed that only one of the three logically possible relations between contrast and prominent positions exists: namely that contrasts in non-prominent positions are always a subset of those in prominent positions. This situation is i...

Predictive accuracy is the sum of two kinds of uncertainty–natural variability and modeling uncertainty. This paper addresses the quantification of predictive accuracy of complex simulation models from two perspectives. First, it recognizes that there is a difference between variability and modeling uncertainty; the former can not be reduced with more test information, while the latter can. We ...