Vol-2669
urn:nbn:de:0074-2669-9

Copyright © 2020 for the individual papers by the papers' authors. Copyright © 2020 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).

CMNA 2020
Computational Models of Natural Argument 2020

Proceedings of the 20th Workshop on Computational Models of Natural Argument
co-located with the 8th International Conference on Computational Models of Argument (COMMA 2020)

Perugia, Italy (and online), September 8th, 2020.

Edited by

Floriana Grasso⁽¹⁾
Nancy L. Green⁽²⁾
Jodi Schneider⁽³⁾
Simon Wells⁽⁴⁾

(1) Department of Computer Science, University of Liverpool, UK
(2) Department of Computer Science, University of North Carolina at Greensboro, US
(3) School of Information Sciences, University of Illinois at Urbana Campaign, US
(4) School of Computing, Edinburgh Napier University, UK

Table of Contents

Programme Committee

A Context-based Argumentation Framework with Values 1-10
Zhe Yu
Transfer Learning with Sentence Embeddings for Argumentative Evidence Classification 11-20
Davide Liga, Monica Palmirani
On Validating Theories of Abstract Argumentation Frameworks: The Case of Bipolar Argumentation Frameworks 21-30
Henry Prakken
Datastores for Argumentation Data 31-40
Simon Wells
Argument Schemes for AI Ethics Education 41-50
Nancy L. Green, L. Joshua Crotts
Argumentation Schemes as Templates? Combining Bottom-up and Top-down Knowledge Representation 51-56
Davide Liga, Monica Palmirani
Persuasive Argument Schemes for Clinical Conflict Resolution: An Empirical Study 57-66
Laura Moss, Derek Sleeman, John Kinsella
Generating Pseudo-Natural Language Explanations for Goal Selection (demo abstract) 67-68
Henrique M. R. Jasinski, Mariela Morveli-Espinoza, Cesar A. Tacla
Towards Automatic Detection of Antithesis 69-73
Nancy L. Green, L. Joshua Crotts
Explaining Legal Decisions Using IRAC 74-83
Trevor Bench-Capon

2020-09-03: submitted by Floriana Grasso, metadata incl. bibliographic data published under Creative Commons CC0
2020-09-11: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|