Dung's Argumentation Framework (AF) has been extended in several directions. Among the
numerous proposed extensions, three of them seem to be of particular interest and have …

Dealing with controversial information is an important issue in several application contexts.
Formal argumentation enables reasoning on arguments for and against a claim to decide on …

The formal characterization of abstract argumentation has allowed the study of many
exciting characteristics of the argumentation process. Nevertheless, while helpful in many …

Abstract Dung's Argumentation Framework (AF) has been extended in several directions. An
interesting extension, among others, is the Epistemic AF (EAF) which allows representing …

Explainable AI Planning (XAIP) aims to develop AI agents that can effectively explain their
decisions and actions to human users, fostering trust and facilitating human-AI collaboration …

We present a novel framework designed to extend model reconciliation approaches,
commonly used in human-aware planning, for enhanced human-AI interaction. By adopting …

A representational limitation of current argumentation frameworks is their inability to deal
with sets of entities and their properties, for example to express that an argument is …

Feature attribution is a fundamental task in both machine learning and data analysis, which
involves determining the contribution of individual features or variables to a model's output …

The notion of similarity has been studied in many areas of Computer Science; in a general
sense, this concept is defined to provide a measure of the semantic equivalence between …

Argumentative discourse rarely consists of opinions whose claims apply universally. As with
logical statements, an argument applies to specific objects in the universe or relations …