Catálogo de publicaciones - libros

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at object-language level. Defeasible argumentation in general and P-DeLP in particular provide a way of modelling non-monotonic inference. From a logical viewpoint, capturing defeasible inference relationships for modelling argument and warrant is particularly important, as well as the study of their logical properties. This paper analyzes two non-monotonic operators for P-DeLP which model the expansion of a given program by adding new weighed facts associated with argument conclusions and warranted literals, resp. Different logical properties for the proposed expansion operators are studied and contrasted with a traditional SLD-based Horn logic. We will show that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworks.

In this paper, we extend the abstract argumentation framework proposed by [1] in order to take into account two kinds of interaction between arguments: a interaction (an argument can help, support another argument) and a interaction (an argument can attack another argument). In this new abstract argumentation framework, called a , we propose a process. With this process, the value of each argument only depends on the value of the arguments which are directly interacting with in the argumentation system.

In this paper, we extend the basic abstract argumentation framework proposed by Dung, by taking into account two independent kinds of interaction between arguments: a defeat relation and a support relation. In that new framework, called a bipolar argumentation framework, we focus on the concept of acceptability and propose new semantics defined from characteristic properties that a set of arguments must satisfy in order to be an output of the argumentation process. We generalize the well-known stable and preferred semantics by enforcing the coherence requirement for an acceptable set of arguments.

This paper addresses the problem of merging beliefs provided by several sources which can be contradictory.

Among the different methods for managing contradictions, this paper focuses on the one which takes into account the number of sources that support a piece of information and their reliability degrees as well. More precisely, this paper presents a modal logic, extending logic, for reasoning with merged beliefs accordingly. It also shows that this logic unifies two different logics that have been defined in the past.

Both in classical logic and in Answer Set Programming, inconsistency is characterized by non existence of a model. Whereas every formula is a theorem for inconsistent set of formulas, an inconsistent program has no answer. Even if these two results seem opposite, they share the same drawback: the knowledge base is useless since one can not draw valid conclusions from it. Possibilistic logic is a logic of uncertainty able to deal with inconsistency in classical logic. By putting on every formula a degree of certainty, it defines a way to compute, with regard to these degrees, a consistent subset of formulas that can be then used in a classical inference process. In this work, we address the treatment of inconsistency in Answer Set Programming by a possibilistic approach that takes into account the non monotonic aspect of the framework.

In previous papers, we have presented a framework for merging structured information in XML involving uncertainty in the form of probabilities, degrees of beliefs and necessity measures [HL04,HL05a,HL05b]. In this paper, we focus on the quality of uncertain information before merging. We first provide two definitions for measuring information quality of individually inconsistent possibilistic XML documents, and they complement the commonly used concept of inconsistency degree. These definitions enable us to identify if an XML document is of or quality when it is inconsistent, as well as enable us to differentiate between documents that have the same degree of inconsistency. We then propose a more general method to measure the quality of an inconsistent possibilistic XML document in terms of a pair of coherence measures.

The Lang-Marquis framework for reasoning in the presence of inconsistencies, which is based on the so-called forget operation, is generalized here. Despite extending the original proposal, a simpler structure is used. A notion of equivalence is introduced which is proven to provide extensionality for the framework. Some other formal properties are also given which illustrate the versatility of the definitions.

In the field of requirements engineering, measuring inconsistency is crucial to effective inconsistency management. A practical measure must consider both the degree and significance of inconsistency in specification. The main contribution of this paper is providing an approach for measuring inconsistent specification in terms of the priority-based scoring vector, which integrates the measure of the degree of inconsistency with the measure of the significance of inconsistency. In detail, for each specification Δ that consists of a set of requirements statements, if is a -level priority set, we define a -dimensional priority-based significance vector to measure the significance of the inconsistency in Δ. Furthermore, a priority-based scoring vector : (Δ)→ N has been defined to provide an ordering relation over specifications that describes which specification is “more essentially inconsistent than” others.

This paper presents a synthesis of works performed on the practical tractability of revision on geographic information within the european REV!GIS project.It surveys di.erent representations of the revision problem as well as di.erent implementations of the adopted stategy: Removed Set Revision (RSR). A comparison of the representation formalisms is provided, a formal and an experimental comparison is conducted on the various implementations on real scale applications in the context of GIS.

Semi-revision is a model of belief change that differs from revision in that a new formula is not always accepted. Later, Fuhrmann defined multiple semi-revision by replacing a new formula with a set of formulae as the new information, which results in a merging operator called a partial meet merging operator. The problem for the partial meet merging operator is that it needs additional information to define a which selects a subset from a set of maximal consistent subbases of an inconsistent knowledge base. In this paper, we will extend multiple semi-revision in the framework of possibilistic logic. The advantage of possibilistic logic is that it provides an ordering relation on formulae in knowledge bases, which makes it easy to define a practically.