Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26518
Title: On the Complexity of Determining Defeat Relations Consistent with Abstract Argumentation Semantics
Authors: Mumford, J
Sassoon, I
Black, E
Parsons, S
Keywords: abstract argumentation;complexity analysis;σ-consistency
Issue Date: 14-Sep-2022
Publisher: IOS Press
Citation: Mumford, J. et al. (2022) 'On the Complexity of Determining Defeat Relations Consistent with Abstract Argumentation Semantics', in Toni, F. et al. (eds.) Frontiers in Artificial Intelligence and Applications, 335, pp. 260 - 271. doi: 10.3233/FAIA220158.
Series/Report no.: Frontiers in Artificial Intelligence and Applications;353
Abstract: Copyright 2022 The authors and IOS Press. Typically in abstract argumentation, one starts with arguments and a defeat relation, and applies some semantics in order to determine the acceptability status of the arguments. We consider the converse case where we have knowledge of the acceptability status of arguments and want to identify a defeat relation that is consistent with the known acceptability data – the σ-consistency problem. Focusing on complete semantics as underpinning the majority of the major semantic types, we show that the complexity of determining a defeat relation that is consistent with some set of acceptability data is highly dependent on how the data is labelled. The extension-based 2-valued σ-consistency problem for complete semantics is revealed as NP-complete, whereas the labelling-based 3-valued σ-consistency problem is solvable within polynomial time. We then present an informal discussion on application to grounded, stable, and preferred semantics.
Description: Presented at Computational Models of Argument Proceedings of COMMA 2022 ((9th International Conference on Computational Models of Argument COMMA 2022, Cardiff, UK, 14-16 September, 2022) Available at https://ebooks.iospress.nl/ISBN/978-1-64368-306-5
URI: https://bura.brunel.ac.uk/handle/2438/26518
DOI: https://doi.org/10.3233/FAIA220158
ISBN: 978-1-64368-306-5 (pbk)
978-1-64368-307-2 (ebk)
ISSN: 0922-6389
Other Identifiers: ORCID iD: Isabel Sassoon https://orcid.org/0000-0002-8685-1054
Appears in Collections:Dept of Computer Science Research Papers

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