Three papers accepted to KR 2020
Three research papers by the Constraint Reasoning and Optimization Group have been accepted for publication in the proceedings of KR 2020, a central European conference in the AI research are of knowledge representation and reasoning

The Constraint Reasoning and Optimization contributes to KR 2020 with three papers focusing on different computational aspects of argumentation:

  • An Answer Set Programming Approach to Argumentative Reasoning in the ASPIC+ Framework, authored by
    Tuomo Lehtonen and Matti Järvisalo together with Johannes P. Wallner (Vienna University of Technology, Austria), develops a direct declarative approach based on answer set programming (ASP) to reasoning in an instantiation of the ASPIC+ framework.  In particular, formal foundations for direct declarative encodings for reasoning in ASPIC+ without preferences are established for several central argumentation semantics, and ASP encodings of semantics for which reasoning about acceptance is NP-hard in ASPIC+ are developed. Empirically, it is shown that the ASP approach scales up to frameworks of significant size, thereby answering the current lack of practical computational approaches to reasoning in ASPIC+ and providing a promising base for capturing further generalizations within ASPIC+. 
  • Smallest Explanations and Diagnoses of Rejection in Abstract Argumentation  by Andreas Niskanen and Matti Järvisalo focuses on two recently proposed complementary notions—explanations and diagnoses—for capturing underlying reasons for rejection in terms of (small) subsets of arguments or attacks. In particular, the work provides tight complexity results for deciding and computing argument-based explanations and diagnoses; identifies that smallest explanations and diagnoses for argumentation frameworks can be computed as so-called smallest unsatisfiable subsets (SMUSes) and smallest correction sets of propositional formulas; and shows empirically that SMUS extractors and maximum satisfiability solvers (computing smallest correction sets) offer effective ways of computing smallest explanations and diagnoses.
  • μ-toksia: An Efficient Abstract Argumentation Reasoner by Andreas Niskanen and Matti Järvisalo describes the μ–toksia argumentation reasoning system that ranked first in all reasoning tasks in the main track of in the most recent International Competition on Computational Models of Argumentation, ICCMA 2019.