Sets of Attacking Arguments for Inconsistent Datalog Knowledge Bases

Bruno Yun; Srdjan Vesic; Madalina Croitoru

doi:10.3233/FAIA200526

Sets of Attacking Arguments for Inconsistent Datalog Knowledge Bases

Bruno Yun^* (Corresponding Author), Srdjan Vesic, Madalina Croitoru

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

6 Citations (Scopus)

2 Downloads (Pure)

Abstract

Logic-based argumentation is a well-known approach for reasoning with inconsistent logic knowledge bases. Such frameworks have been shown to suffer from a major practical drawback consisting of a large number of arguments and attacks. To address this issue, we provide an argumentation framework that considers sets of attacking arguments and provide a theoretical analysis of the new framework with respect to its syntactic and semantic properties. We provide a tool for generating such argumentation frameworks from a Datalog knowledge base and study their characteristics.

Original language	English
Title of host publication	Computational Models of Argument
Editors	Henry Prakken, Stefano Bistarelli, Francesco Santini, Carlo Taticchi
Publisher	IOS Press
Pages	419-430
Number of pages	12
Volume	326
ISBN (Electronic)	9781643681061
DOIs	https://doi.org/10.3233/FAIA200526
Publication status	Published - 4 Sept 2020
Event	Computational Models of Argument : Proceedings of COMMA 2020 - Perugia, Italy Duration: 4 Sept 2020 → 11 Sept 2020

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Publisher	IOS press
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	Computational Models of Argument
Country/Territory	Italy
City	Perugia
Period	4/09/20 → 11/09/20

Keywords

argumentation
datalog
SETAF
Argumentation
Datalog

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10.3233/FAIA200526Licence: CC BY-NC

Yun_et_al_IOS_SetsOfAttackingArguments_VoR
© 2020 The authors and IOS Press. 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). doi:10.3233/FAIA200526
Final published version, 266 KBLicence: CC BY-NC

Cite this

Sets of Attacking Arguments for Inconsistent Datalog Knowledge Bases. / Yun, Bruno (Corresponding Author); Vesic, Srdjan; Croitoru, Madalina.
Computational Models of Argument. ed. / Henry Prakken; Stefano Bistarelli; Francesco Santini; Carlo Taticchi. Vol. 326 IOS Press, 2020. p. 419-430 (Frontiers in Artificial Intelligence and Applications).

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Yun, B, Vesic, S & Croitoru, M 2020, Sets of Attacking Arguments for Inconsistent Datalog Knowledge Bases. in H Prakken, S Bistarelli, F Santini & C Taticchi (eds), Computational Models of Argument. vol. 326, Frontiers in Artificial Intelligence and Applications, IOS Press, pp. 419-430, Computational Models of Argument , Perugia, Italy, 4/09/20. https://doi.org/10.3233/FAIA200526

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Sets of Attacking Arguments for Inconsistent Datalog Knowledge Bases

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Keywords

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