In this paper, we introduce a possibilistic argumentation-based decision making framework which is able to capture uncertain information and exceptions/defaults. In particular, we define the concept of a possibilistic decision making framework which is based on a possibilistic default theory, a set of decisions and a set of prioritized goals. This set of goals captures user preferences related ...

The paper deals with a possibilistic imprecise second-order probability model. It is argued that such models appear naturally in a number of situations. They lead to the introduction of a new type of previsions, called possibilistic previsions, which formally generalise coherent upper and lower previsions. The converse problem is also looked at: given a possibilistic prevision, under what condi...

Possibility theory offers either a qualitative, or a numerical framework for representing uncertainty, in terms of dual measures of pos­ sibility and necessity. This leads to the ex­ istence of two kinds of possibilistic causal graphs where the conditioning is either based on the minimum, or on the product opera­ tor. Benferhat et al. [3] have investigated the connections between min-based grap...

Ranking functions are qualitative degrees of uncertainty ascribed to events charged by uncertainty and taking as their values non-negative integers in the sense of ordinal numbers. Introduced are ranking functions induced by real-valued possibilistic measures and it is shown that different possibilistic measures with identical ranking functions yield the same results when applied in decision pr...

In standard possibilistic logic, prioritized in­ formation are encoded by means of weighted knowledge bases. This paper proposes an exten­ sion of possibilistic logic to deal with partially ordered information which can be viewed as a family of possibilistic knowledge bases. We show that all basic notions of possibilis­ tic logic have natural counterparts when dealing with partially ordered inf...