A Knowledge Base of Argumentation Schemes for Multi-Agent Systems

Carlos Eduardo A. Ferreira, Débora C. Engelmann, Rafael H. Bordini, Joel Luis Carbonera, Alison R. Panisson

Abstract: Argumentation constitutes one of the most significant components of human intelligence. Consequently, argumentation has played a significant role in the community of Artificial Intelligence, in which many researchers study ways to replicate this intelligent behaviour in intelligent agents. In this paper, we describe a knowledge base of argumentation schemes modelled to enable intelligent agents’ general (and domain-specific) argumentative capability. To that purpose, we developed a knowledge base that not only enables agents to reason and communicate with other software agents using a computation model of arguments, but also with humans, using a natural language representation of arguments which results from natural language templates modeled alongside their respective argumentation scheme. To illustrate our approach, we present a scenario in the legal domain where an agent employs argumentation schemes to reason about a crime, deciding whether the defendant intentionally committed t