Possibilitic networks, which are compact representations of possibility distributions, are powerful tools for representing and reasoning with uncertain and incomplete knowledge. According to the operator conditioning is based on, there are two possibilistic settings: quantitative and qualitative. This paper deals with qualitative possibilistic network classifiers under uncertain inputs. More pr...

This paper describes the use of syntactical data fusion to computing possibilistic qualitative decisions. More precisely qualitative possibilistic decisions can be viewed as a data fusion problem of two particular possibility distributions (or possibilistic knowledge bases): the first one representing the beliefs of an agent and the second one representing the qualitative utility. The proposed ...

This paper addresses the problem of merg­ ing uncertain information in the framework of possibilistic logic. It presents several syn­ tactic combination rules to merge possibilis­ tic knowledge bases, provided by different sources, into a new possibilistic knowledge base. These combination rules are first de­ scribed at the meta-level outside the lan­ guage of possibilistic logic. Next, an exte...

In this paper, it is argued that a possibilistic uncertainty model can be used to represent linguistic uncertainty about the states of a system and of its components. Furthermore, the basic properties of the application of this model to classical reliability theory are studied. The notion of the possibilistic reliability of a system or a component is defined. Based upon the concept of a binary ...

Possibilistic logic is a well-known framework for dealing with uncertainty and reasoning under inconsistent knowledge bases. Standard possibilistic logic expressions are propositional logic formulas associated with positive real degrees belonging to [0,1]. However, in practice it may be difficult for an expert to provide exact degrees associated with formulas of a knowledge base. This paper pro...

Possibility theory was initiated by Zadeh in 1978 as an alternative to probability theory. Probability theory is not efficient in the study of those uncertainty situations in which phenomena occur with a small frequency. In such cases it is preferable to apply techniques offered by possibility theory.In foundation of possibility theory one started on a paralel line with probability theory. Rand...

In this technical report, the systematic investigation of lattice-valued possibilistic measures, opened in the first part of this report (cf. Technical Report No. 952, ICS AS CR, December 2005) is pursued and focused towards possibilistic variants of the notions of outer (upper) and lower (inner) possibilistic measures induced by a given partial possibilistic measure. The notion of Lebesgue mea...

Dubois and Prade introduced the mean value of a fuzzy number as a closed interval bounded by the expectations calculated from its upper and lower distribution functions. In this paper introducing the notations of lower possibilistic and upper possibilistic mean values we definine the interval-valued possibilistic mean and investigate its relationship to the interval-valued probabilistic mean. W...

In this paper we define the semantics for capturing possibilistic ordered disjunction programs based on pstable semantics. The pstable semantics, based on paraconsistent logic, allows to treat inconsistency programs. Moreover being closer to possibilistic inference it allows to extend the necessity-values of the clauses to be considered, causing a higher level of comparison at the moment of sel...

In this paper we present a unified (probabilistic/possibilistic) model for resource-constrained project scheduling problem (RCPSP) with uncertain activity durations and a concept of a heuristic approach connected to the theoretical model. It is shown that the uncertainty management can be built into any heuristic algorithm developed to solve RCPSP with deterministic activity durations. The esse...