Robots have become usual collaborators in our daily life. While robotic systems grow to be more and more complex, the need to engineering their software development process grows as well. Traditional approaches that are used in the development process of…

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…

El objetivo central de esta línea de investigación consiste en proponer distintas metodologías formales para representar el conocimiento en diversos sistemas argumentativos.
Como todo sistema simbólico, los sistemas argumentativos emulan el proceso de razonamiento como una manipulación dediversos símbolos. Esto…

Current reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a…

The goal of this work involves the developing of an argumentation-based formalism that an agent could use for constructing plans. In this formalism, agents will have certain knowledge about the world, and a set of actions that they will be…

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…

El análisis de imágenes puede revelar información útil para los usuarios El significativo aumento del uso de imágenes en diferentes campos de la ciencia, medicina, negocios, etc., requiere de mayor poder de procesamiento.
Con el avance en la adquisición de…

One of the key aspects in the design of an architecture for autonomous agents is the way in which beleifs are revised in the face of new information. An intelligent agent must be prepared to handle new information (be it…

We present a socially inspired approach that allows agents in Multi-Agent Systems to speed up their own learning process through communication. Thereby, they are able to trade off impact of knowledge by mutation dependent on the recent performance of the…

Decision tree learning algorithms have been successfully used in knowledge discovery. They use induction in order to provide an appropriate classification of objects in terms of their attributes, inferring decision tree rules. This paper reports on the use of ID3…