XARF: Explanatory Argumentation Rule-Based Framework

Hugo Eduardo Sanches, Ayslan Possebom, Linnyer Beatrys Ruiz Aylon

2025

Abstract

This paper introduces the Explanatory Argumentation Rule-based Framework (XARF), a new approach in Explainable Artificial Intelligence (XAI) designed to provide clear and understandable explanations for machine learning predictions and classifications. By integrating a rule-based system with argumentation theory, XARF elucidates the reasoning behind machine learning outcomes, offering a transparent view into the otherwise opaque processes of these models. The core of XARF lies in its innovative utilization of the apriori algorithm for mining rules from datasets and using them to form the foundation of arguments. XARF further innovates by detailing a unique methodology for establishing attack relations between arguments, allowing for the construction of a robust argumentation structure. To validate the effectiveness and versatility of XARF, this study examines its application across seven distinct machine learning algorithms, utilizing two different datasets: a basic Boolean dataset for demonstrating fundamental concepts and methodologies of the framework, and the classic Iris dataset to illustrate its applicability to more complex scenarios. The results highlight the capability of XARF to generate transparent, rule-based explanations for a variety of machine learning models.

Paper Citation

in Harvard Style

Sanches H., Possebom A. and Aylon L. (2025). XARF: Explanatory Argumentation Rule-Based Framework. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 683-690. DOI: 10.5220/0013193200003929

in Bibtex Style

@conference{iceis25,
author={Hugo Sanches and Ayslan Possebom and Linnyer Aylon},
title={XARF: Explanatory Argumentation Rule-Based Framework},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={683-690},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013193200003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - XARF: Explanatory Argumentation Rule-Based Framework
SN - 978-989-758-749-8
AU - Sanches H.
AU - Possebom A.
AU - Aylon L.
PY - 2025
SP - 683
EP - 690
DO - 10.5220/0013193200003929
PB - SciTePress