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…

Little has been written about the component provision problem (programming plans and domain concepts) for the repositories of knowledge in program understanding systems and reports that specifically address this issue are unknown. Model-driven and plan-driven approaches use repositories where construction…

In this work we analyze the problem of incorporating specificity to characterize defeat in a particular argumentative framework, called observation based defeasible logic programming (ODeLP) [1]. Eficiency is an important issues in ODeLP, since this framework has been de ned…

In todays world where nearly every company is dependent on the Internet to survive, it is not surprising that the role of intrusion detection has become extremely important within the last decade. Intrusion detection involves determining whether some entity has…

Information systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS).…

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…

This paper presents a proposal for an architecture that integrates knowledge discovery systems (automatic acquisition) and knowledge based systems (experts systems). This work formulates considerations over the viability of the implementation of this architecture according to the advance of the…