Argumentative formalisms have been widely recognized as knowledge representation and reasoning tools able to deal with incomplete and potentially contradictory informa- tion. All such formalisms are computationally demanding. Hence, optimizing argumen- tative systems has been approached from di erent views.

In this paper, we build on previous work on Belief Revision operators based on the use of logic programming with Answer Set semantics as a representation language. We present a set of postulates for Answer Set Revision with respect to…

The design of intelligent agents is greatly influenced by the many different models that exist to represent knowledge. It is essential that such agents have computationally adequate mechanisms to manage its knowledge, which more often than not is incomplete and/or…

In this research line we are exploring the possibility of having multiple preference criteria to compare arguments in in Defeasible Argumentation. In this work we are assuming a goaloriented Argumentative System, to which an application or an agent may seek…

El aprendizaje de juegos ha motivado el desarrollo de numerosas estrategias de Inteligencia Artificial. Si bien existen diferentes enfoques, la adaptación al entorno de información es una característica deseable cuando se busca resolver un problema complejo ya que hace innecesaria…