Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Strategic argumentation dialogues for persuasion: framework and experiments based on modelling the beliefs and concerns of the persuadee

Hadoux, Emmanuel, Hunter, Anthony and Polberg, Sylwia ORCID: https://orcid.org/0000-0002-0811-0226 2023. Strategic argumentation dialogues for persuasion: framework and experiments based on modelling the beliefs and concerns of the persuadee. Argument and Computation 14 (2) , pp. 109-161. 10.3233/AAC-210005

[thumbnail of aac_2023_14-2_aac-14-2-aac210005_aac-14-aac210005.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (879kB) | Preview

Abstract

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is "good" in a particular dialogue are the degree to which the intended audience believes the argument and counterarguments, and the impact that the argument has on the concerns of the intended audience. In this paper, we present a framework for modelling persuadees in terms of their beliefs and concerns, and for harnessing these models in optimizing the choice of move in persuasion dialogues. Our approach is based on the Monte Carlo Tree Search which allows optimization in real-time. We provide empirical results of a study with human participants that compares an automated persuasion system based on this technology with a baseline system that does not take the beliefs and concerns into account in its strategy.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: IOS Press
ISSN: 1946-2166
Date of First Compliant Deposit: 20 March 2023
Date of Acceptance: 5 December 2022
Last Modified: 19 Jul 2023 15:05
URI: https://orca.cardiff.ac.uk/id/eprint/157846

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics