Using graph convolutional networks for approximate reasoning with abstract argumentation frameworks: A feasibility study I Kuhlmann, M Thimm
International Conference on Scalable Uncertainty Management, 24-37, 2019
40 2019 A Comparison of ASP-Based and SAT-Based Algorithms for the Contension Inconsistency Measure I Kuhlmann, A Gessler, V Laszlo, M Thimm
International Conference on Scalable Uncertainty Management, 139-153, 2022
10 2022 On the Impact of Data Selection when Applying Machine Learning in Abstract Argumentation I Kuhlmann, T Wujek, M Thimm
Computational Models of Argument, 224-235, 2022
10 2022 An algorithm for the contension inconsistency measure using reductions to answer set programming I Kuhlmann, M Thimm
Scalable Uncertainty Management: 14th International Conference, SUM 2020 …, 2020
10 2020 Algorithms for inconsistency measurement using answer set programming I Kuhlmann, M Thimm
Proceedings of the 19th International Workshop on Non-Monotonic Reasoning …, 2021
9 2021 Graph Neural Networks for Algorithm Selection in Abstract Argumentation. J Klein, I Kuhlmann, M Thimm
ArgML@ COMMA, 81-95, 2022
8 2022 Paraconsistent reasoning for inconsistency measurement in declarative process specifications C Corea, I Kuhlmann, M Thimm, J Grant
Information Systems 122, 102347, 2024
6 2024 Non-Automata Based Conformance Checking of Declarative Process Specifications Based on ASP I Kuhlmann, C Corea, J Grant
International Conference on Business Process Management, 396-408, 2023
5 2023 Comparison of SAT-based and ASP-based Algorithms for Inconsistency Measurement I Kuhlmann, A Gessler, V Laszlo, M Thimm
arXiv preprint arXiv:2304.14832, 2023
4 2023 Computing MUS-based inconsistency measures I Kuhlmann, A Niskanen, M Järvisalo
European Conference on Logics in Artificial Intelligence, 745-755, 2023
3 2023 An ASP-Based Framework for Solving Problems Related to Declarative Process Specifications. I Kuhlmann, C Corea, J Grant
NMR, 129-132, 2023
3 2023 MaxSAT-Based Inconsistency Measurement A Niskanen, I Kuhlmann, M Thimm, M Järvisalo
Proceedings of the 26th European Conference on Artificial Intelligence (ECAI …, 2023
3 2023 Towards Eliciting Attacks in Abstract Argumentation Frameworks I Kuhlmann
Online Handbook of Argumentation for AI 2, 2021
3 2021 Distinguishability in Abstract Argumentation I Kuhlmann, T Rienstra, L Bengel, K Skiba, M Thimm
Proceedings of the International Conference on Principles of Knowledge …, 2021
2 2021 Inconsistency Measurement in LTL I Kuhlmann, C Corea
International Conference on Scalable Uncertainty Management, 217-232, 2024
1 2024 Online Handbook of Argumentation for AI: Volume 2 A Brannstrom, F Castagna, T Duchatelle, M Foulis, T Kampik, I Kuhlmann, ...
arXiv preprint arXiv:2106.10832, 2021
1 2021 Integrating Feedforward Design into a Generative Network to Synthesize Supplementary Training Data for Object Classification I Kuhlmann, V Seib, D Paulus
2021 IEEE International Conference on Autonomous Robot Systems and …, 2021
1 2021 Scratchy: a lightweight modular autonomous robot for robotic competitions R Memmesheimer, I Kuhlmann, M Mints, P Schmidt, C Korbach, ...
2019 IEEE International Conference on Autonomous Robot Systems and …, 2019
1 2019 Increasing Interpretability in Outside Knowledge Visual Question Answering M Upravitelev, C Krauss, I Kuhlmann
International Conference on Knowledge Management in Organizations, 319-330, 2024
2024 Enhancing Abstract Argumentation Solvers with Machine Learning-Guided Heuristics: A Feasibility Study S Hoffmann, I Kuhlmann, M Thimm
Conference on Advances in Robust Argumentation Machines, 185-201, 2024
2024 
Matthias ThimmUniversity of HagenПотвърден имейл адрес: fernuni-hagen.de
