Algorithms for reasoning in a default logic instantiation of assumption-based argumentation

Tuomo Lehtonen, Johannes Peter Wallner, Matti Järvisalo

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Assumption-based argumentation (ABA) is one of the most-studied formalisms for structured argumentation. While ABA is a general formalism that can be instantiated with various different logics, most attention from the computational perspective has been focused on the logic programming (LP) instantiation of ABA. Going beyond the LP-instantiation, we develop an algorithmic approach to reasoning in the propositional default logic (DL) instantiation of ABA. Our approach is based on iterative applications of Boolean satisfiability (SAT) solvers as a natural choice for implementing derivations as entailment checks in DL. We instantiate the approach for deciding acceptance and for assumption-set enumeration in the DL-instantiation of ABA under several central argumentation semantics, and empirically evaluate an implementation of the approach.
Original languageEnglish
Title of host publicationComputational Models of Argument - Proceedings of COMMA 2022
EditorsFrancesca Toni, Sylwia Polberg, Richard Booth, Martin Caminada, Hiroyuki Kido
Number of pages12
ISBN (Electronic)9781643683065
Publication statusPublished - 2022
Event9th International Conference on Computational Models of Argument: COMMA 2022 - Cardiff, United Kingdom
Duration: 14 Sept 202216 Sept 2022

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press


Conference9th International Conference on Computational Models of Argument
Abbreviated titleCOMMA 2022
Country/TerritoryUnited Kingdom
Internet address


  • assumption-based argumentation
  • counterexample-guided abstraction refinement
  • decision procedures
  • default logic
  • SAT
  • structured argumentation

ASJC Scopus subject areas

  • Artificial Intelligence

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