Our research focuses on understanding and solving challenging reasoning tasks for promising approaches to knowledge representation. 

Research projects:

• FWF project A Novel Computational Workflow for Argumentation in AI (started in 2022).
• FWF project Extending Belief Change to Advance Dynamics in Argumentation (2017-2021).

Below you find several research directions of the group.

For an introduction to the topic, you can have a look, e.g., at the Handbook of Formal Argumentation or this article. 

Sample publications of the group

• Abstract Dialectical Frameworks. An Overview. Gerhard Brewka, Stefan Ellmauthaler, Hannes Strass, Johannes P. Wallner, and Stefan Woltran. In Pietro Baroni, Dov Gabbay, Massimiliano Giacomin and Leendert van der Torre, editors, Handbook of Formal Argumentation, chapter 5, pages 237-285. 2018. Link
• Enforcement in Formal Argumentation. Ringo Baumann, Sylvie Doutre, Jean-Guy Mailly, and Johannes P. Wallner. In Dov Gabbay, Massimiliano Giacomin, Guillermo R. Simari, and Matthias Thimm, editors, Handbook of Formal Argumentation, volume 2, chapter 8. 2021.

Sample publications

• Complexity Results and Algorithms for Extension Enforcement in Abstract Argumentation. Johannes P. Wallner, Andreas Niskanen, and Matti Järvisalo. Journal of Artificial Intelligence Research, Vol. 60, pp. 1-40. 2017. Link
• On the complexity of inconsistency measurement. Matthias Thimm and Johannes P. Wallner. Artificial Intelligence, Vol. 275, pp. 411-456. 2019. Link
• Advanced algorithms for abstract dialectical frameworks based on complexity analysis of subclasses and SAT solving. Thomas Linsbichler, Marco Maratea, Andreas Niskanen, Johannes P. Wallner, and Stefan Woltran. Artificial Intelligence, Vol. 307, 103697. Link
• Analyzing the Computational Complexity of Abstract Dialectical Frameworks via Approximation Fixpoint Theory. Hannes Strass and Johannes P. Wallner. Artificial Intelligence, 226:34-74, 2015. Link

Sample publications

• Declarative Algorithms and Complexity Results for Assumption-Based Argumentation. Tuomo Lehtonen, Johannes P. Wallner, and Matti Järvisalo. Journal of Artificial Intelligence Research, Vol. 71, pp. 265-318. 2021. Link
• Reduction-based Approaches to Implement Modgil's Extended Argumentation Frameworks. Wolfgang Dvořák, Sarah A. Gaggl, Thomas Linsbichler, and Johannes P. Wallner. In Thomas Eiter, Hannes Strass, Mirosław Truszczyński and Stefan Woltran, editors, Advances in Knowledge Representation, Logic Programming, and Abstract Argumentation. Essays Dedicated to Gerhard Brewka on the Occasion of His 60th Birthday, pages 249-264. 2015. Link

Sample publications

• Existential Abstraction on Argumentation Frameworks via Clustering. Zeynep G. Saribatur and Johannes P. Wallner. In Meghyn Bienvenu, Gerhard Lakemeyer, and Esra Erdem, editors, Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, KR 2021, pages 549-559, 2021. IJCAI. Link
• Strong Explanations in Abstract Argumentation. Markus Ulbricht and Johannes P. Wallner. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, pages 6496-6504. AAAI Press. Link
• Explaining Non-Acceptability in Abstract Argumentation. Zeynep G. Saribatur, Johannes P. Wallner, and Stefan Woltran. In Giuseppe De Giacomo, Alejandro Catala, Bistra Dilkina, Michela Milano, Senén Barro, Alberto Bugarín, and Jérôme Lang, editors, Proceedings of the Twenty-fourth European Conference on Artificial Intelligence, ECAI 2020, volume 325 of Frontiers in Artificial Intelligence and Applications pages 881-888, 2020. IOS Press. Link

Sample publications

• Ranking Sets of Defeasible Elements in Preferential Approaches to Structured Argumentation: Postulates, Relations, and Characterizations. Jan Maly and Johannes P. Wallner. In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, pages 6435-6443. AAAI Press Link
• Declarative Algorithms and Complexity Results for Assumption-Based Argumentation. Tuomo Lehtonen, Johannes P. Wallner, and Matti Järvisalo. Journal of Artificial Intelligence Research, Vol. 71, pp. 265-318. 2021. Link
• Manipulating Skeptical and Credulous Consequences when Merging Beliefs. Adrian Haret and Johannes P. Wallner. In Francesco Calimeri, Nicola Leone, and Marco Manna, editors, Proceedings of the 16th European Conference on Logics in Artificial Intelligence, JELIA 2019, volume 11468 of Lecture Notes in Computer Science, pages 133-150. Springer. Link