Possibilistic logic offers a convenient tool for handling uncertain or prioritized formulas and coping with inconsistency. Propositional logic formulas are thus associated with weights belonging to a linearly ordered scale. However, especially in case of multiple source information, only partial knowledge may be available about the relative ordering between weights of formulas. In order to cope...

Based on our earlier work on partial logics and extended logic programs Wag91, Wag94, HJW96], and on the possibilistic logic of DLP94], we deene a compositional possibilistic rst-order logic with two kinds of negation as the logical basis of semi-possibilistic and possibilis-tic logic programs. We show that in the same way as the minimal model semantics of relational databases can be reened to ...

This paper uses the concept of possibilistic risk aversion to propose a new approach for portfolio selection in fuzzy environment. Using possibility theory, the possibilistic mean, variance, standard deviation and risk premium of a fuzzy number are established. Possibilistic Sharpe ratio is defined as the ratio of possibilistic risk premium and possibilistic standard deviation of a portfolio. T...

This paper presents a latest survey of different technologies using fuzzy clustering algorithms. Clustering approach is widely used in biomedical field like image segmentation. A different methods are used for medical image segmentation like Improved Fuzzy C Means(IFCM), Possibilistic C Means(PCM),Fuzzy Possibilistic C Means(FPCM), Modified Fuzzy Possibilistic C Means(MFPCM) and Possibilistic F...

This paper deals with the querying of possibilistic relational databases, by means of possibilistic queries whose general form is: "to what extent is it possible that the answer to Q satisfies property P". Here, we consider cardinality-based queries (in this case, property P is about cardinality) for which a processing technique is proposed, which avoids computing all the worlds attached to the...

This article is a first step in the direction of extending possibilistic planning to account for incomplete and imprecise knowledge of the world state. Fundamental definitions are given and the possibilistic planning problem is recast in this new setting. Finally, it is shown that, under certain conditions, possibilistic planning with imprecise and incomplete state descriptions is no harder tha...

Inconsistent knowledge bases usually are regarded as an epistemic hell that have to be avoided at all costs. However, many times it is di cult or impossible to stay away of managing inconsistent knowledge bases. In this paper, we introduce an argumentation-based approach in order to manage inconsistent possibilistic knowledge bases. This approach will be exible enough for managing inconsistent ...

In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in feature space based on the possibilistic approach to clustering. The proposed algorithms retain the properties of the possibilistic clustering, working as density estimators in feature space and showing high robustne...

Possibilistic ATMS are truth maintenance systems oriented towards hypothetical reasoning where both assumptions and justifications can bear an uncertainty weight. Uncertainty is represented in the framework of possibility theory. In possibilistic logic uncertain clauses are handled as such and then in possibilistic ATMS the management of uncertainty is not separated from the other classical cap...