Harnessing incremental answer set solving for reasoning in assumption-based argumentation

Tuomo Lehtonen, Johannes Peter Wallner, Matti Järvisalo

Research output: Contribution to journalArticlepeer-review


Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for developing effective algorithms for reasoning tasks in the logic programming fragment of ABA that are presumably hard for the second level of the polynomial hierarchy, including skeptical reasoning under preferred semantics as well as preferential reasoning. In particular, we develop non-trivial counterexample-guided abstraction refinement procedures based on incremental ASP solving for these tasks. We also show empirically that the procedures are significantly more effective than previously proposed algorithms for the tasks.
Original languageEnglish
Pages (from-to)717 - 734
Number of pages18
JournalTheory and Practice of Logic Programming
Issue number6
Publication statusPublished - 10 Nov 2021


  • algorithms
  • Answer set programming
  • assumption-based argumentation
  • experimental evaluation
  • incremental answer set solving
  • structured argumentation
  • Algorithms
  • Incremental answer set solving
  • Assumption-based argumentation
  • Structured argumentation
  • Experimental evaluation

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics


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