Auteurs : Moraitis, Pavlos
Publication : 29 janvier 2019

Computational argumentation is an important domain in the field of Artificial Intelligence.

Accumulated over more than two decades, there is nowadays a vast literature on various aspects of argumentation, such as abstract argumentation frameworks and their semantics, structured argumentation frameworks, and more recently on a particular topic called argumentation dynamics. Also over the last two decades there has been an increasing interest in applying argumentation to analyze and solve practical problems in the area of Artificial Intelligence (AI). The natural link of argumentation to human reasoning makes Computational Argumentation an appropriate framework for applications in AI. Moreover argumentation satisfies the need for explainable AI.

A wide class of applications of argumentation concerns decision problems in dynamic and incomplete, or uncertain, environments. In this talk we will start by presenting some basic notions in computational argumentation and then we will present an abstract argumentation framework called “Control Argumentation Frameworks (CAFs)” and a structured argumentation framework called “Logic Programming with Priorities (LPP)” and its associated system GORGIAS and we will show how they can be used for modeling autonomous agents reasoning. Then we will present how they can be used for modeling multi-agent dialogues (e.g. negotiation, deliberation). Finally we will show how these theoretical frameworks can be used for modeling decision making problems under incomplete, conflicting and contextual knowledge in real world applications.