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Graph Neural Networks for Algorithm Selection in Abstract Argumentation., , and . ArgML@COMMA, volume 3208 of CEUR Workshop Proceedings, page 81-95. CEUR-WS.org, (2022)On the Impact of Data Selection when Applying Machine Learning in Abstract Argumentation., , and . COMMA, volume 353 of Frontiers in Artificial Intelligence and Applications, page 224-235. IOS Press, (2022)Revision and Conditional Inference for Abstract Dialectical Frameworks., , , , and . KR, page 345-355. (2021)Measuring Inconsistency over Sequences of Business Rule Cases., , and . KR, page 655-660. (2021)Measuring Inconsistency with the Tableau Method., and . FLAP, 10 (5): 643-691 (2023)Joining Formal and Cognitive Reasoning., , , and . FLAP, 10 (2): 115-119 (2023)Algorithmic Approaches to Computational Models of Argumentation.. FQAS, volume 11529 of Lecture Notes in Computer Science, page 18-21. Springer, (2019)Measuring Inconsistency in Declarative Process Specifications., , and . BPM, volume 13420 of Lecture Notes in Computer Science, page 289-306. Springer, (2022)Reasoning with maximal consistent signatures., and . CoRR, (2024)Characterising Serialisation Equivalence for Abstract Argumentation., , and . ECAI, volume 392 of Frontiers in Artificial Intelligence and Applications, page 3340-3347. IOS Press, (2024)