Five workshop papers accepted at COMMA 2022


Five workshop papers were accepted for presentation at COMMA 2022 in Cadiff, Wales.

Abstracts of the papers

A Labeling-Based Backtracking Solver for Abstract Argumentation
by Lukas Kinder, Matthias Thimm, Bart Verheij
Abstract: THEIA is a labeling-based system computing the complete extensions of an abstract argumentation framework. Like other backtracking solvers, THEIA does this by repeatedly choosing an argument and label it until either a contradiction with respect to the labels is reached or a complete extension is found. THEIA reduces the number of backtracking steps needed by using propagation techniques that use a larger set of labels. These labels keep track of arguments that cannot be labeled IN, OUT or UNDEC during a state in the search. THEIA is also using an extensive look-ahead strategy to prune branches. It is shown that THEIA outperforms related labeling-based backtracking solvers by the use of more sophisticated propagation and pruning rules and the forward looking strategy.
Workshop: SAFA 2022
More information about SAFA 2022
Argumentation-based Causal and Counterfactual Reasoning
by Lars Bengel, Lydia Blümel, Tjitze Rienstra and Matthias Thimm
Abstract: In this paper we present a model for argumentative causal and counterfactual reasoning in a logical setting. Causal knowledge is represented in this system using Pearl’s causal model of a set of structural equations and a set of assumptions expressed in propositional logic. Queries concerning observations or actions can be answered by constructing an argumentation framework and determining its extensions. For counterfactual queries we propose an argumentation-based implementation of the twin network method and analyse its expressiveness.
Workshop: ArgXAI 2022
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Realisability of Ranking-based Semantics
by Kenneth Skiba, Matthias Thimm, Tjitze Rienstra, Jesse Heyninck, Gabriele Kern-Isberner
Abstract: In this work, we discuss the realisability problem for ranking-based se-mantics in the area of abstract argumentation. So, for a given ranking and ranking-based semantics, we want to find an AF s.t. the selected ranking-based semantics induces our ranking when applied to the AF. We show that this question can be answered trivially with yes for a number of ranking-based semantics, i.e. for every ranking we can find such an AF. In addition to the discussion about the realisability problem, we also introduce a new equivalence notion for argumentation frameworks. We call two AFs ranking equivalent if they have the same ranking for a ranking-based semantics.
Workshop: SAFA 2022
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Graph Neural Networks for Algorithm Selection in Abstract Argumentation
by Jonas Klein, Isabelle Kuhlmann and Matthias Thimm
Abstract: We address the task of selecting the fastest algorithm, in terms of runtime, for determining skeptical acceptance under preferred semantics in abstract argumentation frameworks out of a set of multiple algorithms by means of machine learning. To be precise, we examine four “classical” machine learning techniques, as well as three graph neural networks, and compare all of these approaches with regard to both prediction accuracy and the total amount of time the selected algorithms require to solve a given test set in an experimental analysis. Our set of algorithms includes three solvers from the International Competition on Computational Models of Argumentation. Our results demonstrate that graph neural networks are a promising method for algorithm selection in abstract argumentation, as two out of three neural network models outperform all four classical machine learning approaches.
Workshop: ArgML 2022

More information about ArgML 2022

Explaining Argument Acceptance in ADFs
by Tjitze Rienstra, Jesse Heyninck, Gabriele Kern-Isberner, Kenneth Skiba, Matthias Thimm
Abstract: We present a dialogical proof theory for credulous acceptance in abstract dialectical frameworks under the preferred semantics. Our approach is motivated by the need to explain why an argument is accepted. The proof theory defines a set of rules for a dialogue between a proponent and opponent exchanging propositional formulas. The proponent takes on the role of trying to prove that the argument in question is acceptable, and the opponent takes on the role of exhaustively challenges the proponent's moves, with a dialogue where the proponent wins represents a proof that the argument in question is accepted.
Workshop: ArgXAI 2022