An argumentation framework with uncertainty management designed for dynamic environments

Nowadays, data intensive applications are in constant demand and there is need of computing environments with better intelligent capabilities than those present in today's Database Management Systems (DBMS). To build such systems we need formalisms that can perform complicate inferences, obtain the appropriate conclusions, and explain the results. Research in argumentation could provide results in this direction, providing means to build interactive systems able to reason with large databases and/or di erent data sources. In this paper we propose an argumentation system able to deal with explicit uncertainty, a vital capability in modern applications. We have also provided the system with the ability to seamlessly incorporate uncertain and/or contradictory information into its knowledge base, using a modular upgrading and revision procedure Presentado en el X Workshop Agentes y Sistemas Inteligentes Red de Universidades con Carreras en Informática (RedUNCI)