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Computationally viable handling of beliefs in arguments for persuasion

Hadoux, E; Hunter, A; (2017) Computationally viable handling of beliefs in arguments for persuasion. In: Proceedings of the 28th International Conference on Tools with Artificial Intelligence (ICTAI). (pp. pp. 319-326). IEEE Green open access

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Abstract

Computational models of argument are being developed to capture aspects of how persuasion is undertaken. Recent proposals suggest that in a persuasion dialogue between some agents, it is valuable for each agent to model how arguments are believed by the other agents. Beliefs in arguments can be captured by a joint belief distribution over the arguments and updated as the dialogue progresses. This information can be used by the agent to make more intelligent choices of move in the dialogue. Whilst these proposals indicate the value of modelling the beliefs of other agents, there is a question of the computational viability of using a belief distribution over all the arguments. We address this problem in this paper by presenting how probabilistic independence can be leveraged to split this joint distribution into an equivalent set of distributions of smaller size. Experiments show that updating the belief on the split distribution is more efficient than performing updates on the joint distribution.

Type: Proceedings paper
Title: Computationally viable handling of beliefs in arguments for persuasion
Event: 28th International Conference on Tools with Artificial Intelligence
Location: San Jose, CA, USA
Dates: 06 November 2016 - 08 November 2016
ISBN-13: 9781509044597
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICTAI.2016.53
Publisher version: http://dx.doi.org/10.1109/ICTAI.2016.0056
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Computational modeling, Proposals, Probabilistic logic, Artificial intelligence, Hypertension, Random variables, Conferences
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1549757
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