The ability of an agent to make quick, rational decisions in an uncertain environment is paramount for its applicability in realistic settings. Markov Decision Processes (MDP) provide such a framework, but can only model uncertainty that can be expressed as probabilities. Possibilistic counterparts of MDPs allow to model imprecise beliefs, yet they cannot accurately represent probabilistic sour...

We show a hybrid probabilistic and possibilistic model for assessing the risk of a service level agreement for a computing task in a cluster/grid environment. Using the predictive probabilistic approach we develop a framework for resource management in grid computing, and by introducing an upper limit for the number of failures we approximate the probability that a particular computing task is ...

The ability of an agent to make quick, rational decisions in an uncertain environment is paramount for its applicability in realistic settings. Markov Decision Processes (MDP) provide such a framework, but can only model uncertainty that can be expressed as probabilities. Possibilistic counterparts of MDPs allow to model imprecise beliefs, yet they cannot accurately represent probabilistic sour...

In this paper, the concept of possibilistic ev­ idence which is a possibility distribution as well as a body of evidence is proposed over an infinite universe of discourse. The in­ ference with possibilistic evidence is investi­ gated based on a unified inference framework maintaining both the compatibility of con­ cepts and the consistency of the probability logic.

In this paper a class of optimization problems with uncertain linear constraints is discussed. It assumed that the constraint coefficients are random vectors whose probability distributions only partially known. Possibility theory used to model imprecise probabilities. one interpretation, possibility distribution (a membership function fuzzy set) in set coefficient realizations induces necessit...

logistic regression models are frequently used in clinicalresearch and particularly for modeling disease status and patientsurvival. in practice, clinical studies have several limitationsfor instance, in the study of rare diseases or due ethical considerations, we can only have small sample sizes. in addition, the lack of suitable andadvanced measuring instruments lead to non-precise observatio...

Fredholm and Volterra nonlinear possibilistic integral equations In this paper we study the functional obtained from classical of second kind, by replacing there linear Lebesgue with integral.