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


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
EditorsHenry Prakken, Stefano Bistarelli, Francesco Santini, Carlo Taticchi
PublisherIOS Press
Number of pages12
ISBN (Electronic)9781643681061
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


ConferenceComputational Models of Argument


  • argumentation
  • datalog
  • Argumentation
  • Datalog

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