Hunter, A;
(2020)
Reasoning with inconsistent knowledge using the epistemic approach to probabilistic argumentation.
In:
Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning.
(pp. pp. 496-505).
IJCAI Organization: Rhodes, Greece.
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Abstract
Structured argumentation involves drawing inferences from knowledge in order to construct arguments and counterarguments. Since knowledge can be uncertain, we can use a probabilistic approach to representing and reasoning with the knowledge. Individual arguments can be constructed from the knowledge, with the belief in each argument determined just from the belief in the formulae appearing in the argument. However, if the original knowledgebase is inconsistent, this does not take into account the counterarguments that can be constructed. We therefore need a wider perspective that revises the belief in individual arguments in order to take into account the counterarguments. To address this need, we present a framework for probabilistic argumentation that uses relaxation methods to give a coherent view on the knowledge, and thereby revises the belief in the arguments that are generated from the knowledge.
| Type: | Proceedings paper |
|---|---|
| Title: | Reasoning with inconsistent knowledge using the epistemic approach to probabilistic argumentation |
| Event: | KR2020: 17th International Conference on Principles of Knowledge Representation and Reasoning |
| ISBN-13: | 978-0-9992411-7-2 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.24963/kr.2020/50 |
| Publisher version: | https://doi.org/10.24963/kr.2020/50 |
| 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. |
| 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/10128969 |
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