Vol-3208
urn:nbn:de:0074-3208-1

Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

ArgML 2022
Argumentation & Machine Learning

Proceedings of the 1st Workshop on Argumentation & Machine Learning
co-located with 9th International Conference on Computational Models of Argument (COMMA 2022)

Cardiff, Wales, September 13th, 2022.

Edited by

Isabelle Kuhlmann⁽¹⁾
Jack Mumford⁽²⁾
Stefan Sarkadi⁽³⁾

(1) Artificial Intelligence Group, University of Hagen, Germany
(2) Department of Computer Science, University of Liverpool, UK
(3) Department of Informatics, King's College London, UK

Table of Contents

Summary: There were 9 papers submitted for peer-review to this workshop. Out of these, 7 papers were accepted for this volume.
Programme Committee

Argumentation-based Explainable Machine Learning (ArgEML): a Real-life Use Case on Gynecological Cancer 1-13
Nicoletta Prentzas, Athena Gavrielidou, Marios Neofytou, Antonis Kakas
Everyday Argumentative Explanations for Classification 14-26
Jowan van Lente, Annemarie Borg, Floris Bex
Optimizing Language Models for Argumentative Reasoning 27-44
Luke Thorburn, Ariel Kruger
Machine Coaching with Proxy Coaches 45-64
Vasileios Theodoros Markos, Marios Thoma, Loizos Michael
Online Incremental Learning with Abstract Argumentation Frameworks 65-80
Hamed Ayoobi, Ming Cao, Rineke Verbrugge, Bart Verheij,
Graph Neural Networks for Algorithm Selection in Abstract Argumentation 81-95
Jonas Klein, Isabelle Kuhlmann, Matthias Thimm
Learning Gradual Argumentation Frameworks using Meta-heuristics 96-108
Nico Potyka, Mohamad Bazo, Jonathan Spieler, Steffen Staab,

2022-09-07: submitted by Jack Mumford, metadata incl. bibliographic data published under Creative Commons CC0
2022-09-10: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|