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 proceedingConference contribution

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 languageEnglish
Title of host publicationComputational Models of Argument
PublisherIOS Press
Pages419-430
Number of pages12
Volume326
DOIs
Publication statusPublished - 4 Sep 2020
EventComputational Models of Argument : Proceedings of COMMA 2020 - Perugia, Italy
Duration: 4 Sep 202011 Sep 2020

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS press
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

ConferenceComputational Models of Argument
CountryItaly
CityPerugia
Period4/09/2011/09/20

Keywords

  • argumentation
  • datalog
  • SETAF

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