Explaining black-box classification models is a hot topic in AI, with the overall goal of
improving trust in decisions made by such models. Several works have been done and …

This paper explores the computation of explanations in the specific context of abstract
argumentation. The explanations that we define are designed to be visual, in the sense that …

Abstract argumentation is an important research area in AI. It is mainly about the
acceptability of arguments in an argumentation framework. The classical notion of defense …

Argumentation is a formalism allowing to reason with contradictory information by modeling
arguments and their interactions. There are now an increasing number of gradual semantics …

This paper explores the definition of questions and the computation of explanations in
general, and in the specific context of abstract argumentation. We aim at 1) defining a …

Over the recent years there is a growing move towards explainable AI (XAI). The widespread
use of AI systems in a large variety of applications that support human's decisions leads to …

Modeling contrastive explanations for the use in artificial intelligence (AI) applications is an
important research branch within the field of explainable AI (XAI). However, most of the …

Interpretability has become an essential topic for artificial intelligence in some high-risk
domains such as healthcare, bank and security. For commonly-used tabular data, traditional …

With the growing usage of artificial intelligence (AI) in daily life, explainable systems become
more important. Explainable AI (XAI), which is a set of tools and frameworks to help you …

This paper defines visual explanations to the Verification Problem in argumentation, that is,
of why a set of arguments is or is not acceptable under a given semantics. These …