Reasoning over Assumption-Based Argumentation Frameworks via Direct Answer Set Programming Encodings

  • Tuomo Lehtonen University of Helsinki
  • Johannes P. Wallner Vienna University of Technology
  • Matti Järvisalo University of Helsinki


Focusing on assumption-based argumentation (ABA) as a central structured formalism to AI argumentation, we propose a new approach to reasoning in ABA with and without preferences. While previous approaches apply either specialized algorithms or translate ABA reasoning to reasoning over abstract argumentation frameworks, we develop a direct approach by encoding ABA reasoning tasks in answer set programming. This significantly improves on the empirical performance of current ABA reasoning systems. We also give new complexity results for reasoning in ABA+, suggesting that the integration of preferential information into ABA results in increased problem complexity for several central argumentation semantics.

AAAI Technical Track: Knowledge Representation and Reasoning