A solution of problems in multiagent systems involves representing beliefs of agents immersed in dynamic environments. Observation-based Defeasible Logic Programming (ODeLP) is an argument-based logic programming language that is used to represent an agent’s knowledge in the context of a…

Descoberta de Conhecimento em Bases de Dados" ("Knowledge Discovery in Databases", KDD) é um processo composto de várias fases iniciando com a coleta de dados para o problema e finalizando com a avaliação dos resultados finais. Este trabalho objetiva mostrar…

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…

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…

En [2] Gerhard Brewka realizó una reconstrucción de la Teoría de Disputación Formal de Nicholas Rescher [5]. En su trabajo, Brewka completó la formalización de la presentación de Dialectics:
A Controversy-Oriented Approach to the Theory 01 Knowledge. El formalismo no..monótono…

Knowledge acquisition for systems based on knowledge can be called knowledge engineering, according to Feigenbaum (1980) who used the term to describe the reduction of a wide context of knowledge for a set of facts and rules. The term Knowledge…

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality…

Frequently we become amazed with the increasing number of problems to be solved that fiourish while facing daily activities. Often, related to these problems we llave also an incredible amount oí data. Since we cannot allways afford time and resources…

This work extends the semantics and implementation of fuzzy prolog presented in [VGM02] in order to include Default Knowledge capability. The new semantic allows non-uniform default assumptions and has Closed World Assumption (CWA) and Open World Assumption (OWA) as particular…