The notion of context and its importance in knowledge representation and nonmonotonic reasoning was first discussed in Artificial Intelligence by John McCarthy.
Ever since, contexts have found many applications in developing knowledge-based reasoning systems.
Defeasible argumentation has gained wide acceptance…

The problem of speeding up ínference has proved to be important in argumentative systems. When computing dialectical structures, several paths are searched (called argumentation lines), many of which will eventually prove useless. Morover, the performance of backward chainers degrades quickly…

Humans have always been intrigued by their ability to reason. We have constantly attempted to emulate this process, trying almost everything, from physiological explanations, to sociological accounts. The approach with possibly the longest tradition conceives this process as a mere…

The Semantic Web purports to give computeraccessible meaning to the content of the World Wide Web. The rationale behind this project is to create an environment where all this information could be freely exchanged among diverse entities, yet retaining its…

Collaborative systems are becoming a widely used tool particularly among professional communities and research groups. They provide a suitable context for distributed people working on the same subject to concentrate their work in a shared place to which everyone has…

The design of intelligent agents is a key issue for many applications. Since there is no universally accepted definition of intelligence, the notion of rational agency was proposed by Russell as an alternative for the characterization of intelligent agency.
A…

This article presents the confluence of two general ideas: Defeasible Logic Programming (DeLP, an argumentation based formalism for representing knowledge and reasoning) and Abduction in logic. In first place, we introduce a framework that formally states the problem of doing…

The development of systems with the ability to reason about change notion and actions has been of great importance for the artificial intelligence community. The definition and implementation of systems capable of managing defeasible, incomplete, unreliable, or uncertain information has…

Defeasible argumentation is one of the approaches that attempt to address the challenges arising when we reason defeasibly, with several formalisms in the literature reaching a mature state. Nowadays, several of them started shifting their semantics towards a dialectical characterization.…

In the last decade several ways to formalize defeasible reasoning have been studied. A particular approach, defeasible argumentation, has been particularly successful to achieve this goal.
The inference process of argument-based systems is based on the interaction of ar- guments…