Many works in the past showed that human judgments of uncertainty do not conform very well to Probability Theory. The present paper reports four experiments that were conducted in order to evaluate if human judgments of uncertainty conform better to Possibility Theory. At first, two experiments investigate the descriptive properties of some basic possibilistic measures. Then a new measurement a...

In this paper, we survey some quantitative and qualitative approaches to uncertainty management based on possibility theory and present a logical framework to integrate them. The semantics of the logic is based on the Dempster’s rule of conditioning for possibility theory. It is then shown that classical modal logic, conditional logic, possibilistic logic, quantitative modal logic and qualitati...

Possibility theory offers a qualitative framework for modeling decision under uncertainty. In this setting, pessimistic and optimistic decision criteria have been formally justified. The computation by means of possibilistic logic inference of optimal decisions according to such criteria has been proposed. This paper presents an Answer Set Programming (ASP)-based methodology for modeling decisi...

Investigated are possibilistic distributions taking as their values sequences from the infinite Cartesian product of identical copies of a fixed finite subset of the unit interval of real numbers. Uniform and lexicographic partial orderings on the space of these sequences are defined and the related complete lattices introduced. Lattice-valued entropy function is defined in the common pattern f...

In search of semantic richer and more flexible database modelling and database querying techniques, different approaches based on fuzzy set theory have been developed. Among the most successful approaches are the possibilistic and similarity based models. More recently, extended possibilistic logic and various extensions to fuzzy sets have been applied to further enrich flexible database models...

Uncertain information is present in many real applications e.g., medical domain, weather forecast, etc. The most common approaches for leading with this information are based on probability however some times; it is difficult to find suitable probabilities about some events. In this paper, we present a possibilistic logic programming approach which is based on possibilistic logic and PStable se...

Probability assessments of events are often linguistic in nature. We model them by means of possibilistic probabilities (a version of Zadeh’s fuzzy probabilities with a behavioural interpretation) with a suitable shape for practical implementation (on a computer). Employing the tools of interval analysis and the theory of imprecise probabilities we argue that the verification of coherence for t...