This paper presents some results concerning the qualitative behaviour of possibilistic networks. The behaviour of singly connected networks is analysed, providing the founda-tions for qualitative reasoning about changes in possibility values in both predictive and evidential directions. The problems inherent in handling multiply connected networks are also discussed, and a possible solution is proposed. The behaviour of qualitative possibilistic networks is compared to qualitative probabilistic networks, and an example of the kind of reasoning that is permitted by the use of these networks is provided
International audiencePossibilistic networks offer a qualitative approach for modeling epistemic unc...
AbstractIn designing a Bayesian network for an actual problem, developers need to bridge the gap bet...
In designing a Bayesian network for an actual problem, developers need to bridge the gap between th...
This paper extends previous work on propagating qualitative uncertainty in networks in which a gener...
This paper extends previous work on propagating qualitative uncertainty in networks in which a gener...
International audienceThis paper presents a study of the links between two different kinds of knowle...
AbstractPossibilistic logic bases and possibilistic graphs are two different frameworks of interest ...
A probabilistic network consists of a graphical representation (a directed graph) of the important v...
AbstractPossibilistic networks and possibilistic logic are two standard frameworks of interest for r...
International audiencePossibilistic logic bases and possibilistic graphs are two different framework...
AbstractQualitative probabilistic networks were designed to overcome, to at least some extent, the q...
Abstract—Possibilistic networks are belief graphical models based on possibility theory. This paper ...
International audiencePossibilistic networks are important tools for modelling and reasoning, especi...
AbstractAmong the several representations of uncertainty, possibility theory allows also for the man...
AbstractQualitative probabilistic networks (QPNs) are basically qualitative derivations of Bayesian ...
International audiencePossibilistic networks offer a qualitative approach for modeling epistemic unc...
AbstractIn designing a Bayesian network for an actual problem, developers need to bridge the gap bet...
In designing a Bayesian network for an actual problem, developers need to bridge the gap between th...
This paper extends previous work on propagating qualitative uncertainty in networks in which a gener...
This paper extends previous work on propagating qualitative uncertainty in networks in which a gener...
International audienceThis paper presents a study of the links between two different kinds of knowle...
AbstractPossibilistic logic bases and possibilistic graphs are two different frameworks of interest ...
A probabilistic network consists of a graphical representation (a directed graph) of the important v...
AbstractPossibilistic networks and possibilistic logic are two standard frameworks of interest for r...
International audiencePossibilistic logic bases and possibilistic graphs are two different framework...
AbstractQualitative probabilistic networks were designed to overcome, to at least some extent, the q...
Abstract—Possibilistic networks are belief graphical models based on possibility theory. This paper ...
International audiencePossibilistic networks are important tools for modelling and reasoning, especi...
AbstractAmong the several representations of uncertainty, possibility theory allows also for the man...
AbstractQualitative probabilistic networks (QPNs) are basically qualitative derivations of Bayesian ...
International audiencePossibilistic networks offer a qualitative approach for modeling epistemic unc...
AbstractIn designing a Bayesian network for an actual problem, developers need to bridge the gap bet...
In designing a Bayesian network for an actual problem, developers need to bridge the gap between th...