Argumentation-based Approaches to Paraconsistency
Argumentation theory has been described as “a core study within artificial intelligence” (T.Bench-Capon and P.Dunne, “Argumentation in artificial intelligence”, Journal of Artificial Intelligence 171(10):619–641, 2007). Among others, it is a standard method for modeling debates, dialogues, persuasion, and defeasible reasoning through arguments and counter-arguments. Logical (or deductive) argumentation is a branch of argumentation theory in which arguments have a specific structure, and their validity is usually justified by some core logic. In this course we shall review the basic ideas behind logical argumentation and show how they can be used for obtaining some robust paraconsistent logics. In particular, we shall describe the primary approaches to logical argumentation (assumption-based, sequent-based, the ASPIC system, etc), recall some of the basic properties of the paraconsistent entailment relations that are induced by them, show correspondence to related AI methods such as inferences from maximally consistent sets of premises, and demonstrate dynamic proof-theoretical methods for argumentation-based reasoning in the presence of contradictions.