The process of constructing and evaluating arguments for and against claims is pervasive in our everyday lives, e.g. in the ``letters to the editor'' of newspapers, when seeing your doctor, when doing academic research, when making everyday decisions… etc. The study of argumentation dates back to Classical Indian and Greek philosophy, and is now studied in psychology, logic and computer science. Mathematical and logical models of argumentation have been developed over the last few decades to meet the needs of the artificial intelligence community, in particular the need for machines to reason transparently with conflicting and incomplete information, in a way that facilities human-machine interaction. Argumentation theory has since been applied to a wide range of fields such as nonmonotonic logics, uncertain reasoning, decision theory, machine learning and multi-agent systems.
In this talk, I will outline the motivations and history of argumentation theory, and explain how argumentation provides a graphical and dialectical representation of nonmonotonic reasoning. I will also overview selected current research topics in argumentation theory, in particular its relationship to nonmonotonic logics, the use of preferences to reason about values, and formal aspects of dialogical argumentation.