Authors:
Carlos Ferreira
1
;
Débora Engelmann
2
;
Rafael Bordini
3
;
Joel Carbonera
1
and
Alison Panisson
4
Affiliations:
1
Informatics Institute, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
;
2
Integrated Faculty of Taquara (FACCAT), Taquara, Brazil
;
3
School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
;
4
Department of Computing, Federal University of Santa Catarina, Araranguá, Brazil
Keyword(s):
Multi-Agent Systems, Argumentation, Explainable AI.
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
he crime or not, a decision that could significantly impact the severity of the sentence handed down by a legal authority. Once a conclusion is reached, the agent provides a natural language explanation of its reasoning.
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