Hunter, A;
(2020)
Generating instantiated argument graphs from probabilistic information.
In:
Frontiers in Artificial Intelligence and Applications.
(pp. pp. 769-776).
IOS Press
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Abstract
The epistemic approach to probabilistic argumentation assigns belief to arguments. To better understand this approach, we consider structured arguments. Our approach is to start with a probability distribution, and generate an argument graph containing structured arguments with a probability assignment. We construct arguments directly from the probability distribution, rather than a knowledgebase, and then consider methods for selecting the arguments and counterarguments to present in the argument graph. This provides mechanisms for managing uncertainty in argumentation, and for argument-based explanations of probability distributions (that might come from data or from beliefs of an agent).
| Type: | Proceedings paper |
|---|---|
| Title: | Generating instantiated argument graphs from probabilistic information |
| Event: | ECAI 2020 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3233/FAIA200165 |
| Publisher version: | https://doi.org/10.3233/FAIA200165 |
| Language: | English |
| Additional information: | This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). See: https://creativecommons.org/licenses/by-nc/4.0/deed.en |
| UCL classification: | UCL 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: | https://discovery.ucl.ac.uk/id/eprint/10112069 |
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