IK.

Research output · 2019—2026

Publications

Journal articles, conference and workshop papers, handbook contributions, and doctoral dissertation.

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2026

  1. Guiding Admissibility Solvers via Co-Admissibility Predictions. Sandra Hoffmann, Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 11th International Conference on Computational Models of Argument (COMMA 2026), 2026.

  2. Measuring Inconsistency in STL Specifications. Carl Corea, Isabelle Kuhlmann, Karen Leung, John Grant, Matthias Thimm. Proceedings of the 10th International Workshop on Artificial Intelligence for Business Process Management (AI4BPM 2026), co-located with the 24th International Conference on Business Process Management (BPM 2026), 2026.

2025

  1. Exploring Desirable Configurations in Global Logistics with Heuristic Search in Answer Set Programming. Olcay Altay-Kern, Emmanuelle Dietz, Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning (KR 2025), 2025.

  2. Diagnosing Non-Executable Plans via Inconsistency Metrics: A KR-Inspired Perspective for Cognitive Robotics. Isabelle Kuhlmann, Mark O. Mints, Peer Neubert, Matthias Thimm. Proceedings of the 13th International Cognitive Robotics Workshop, 2025.

  3. Algorithmic Approaches for Inconsistency Measurement. Isabelle Kuhlmann. Doctoral dissertation, 2025.

  4. A MaxSAT-Based Approach for Computing Inconsistency Degrees in Linear Temporal Logic on Fixed Traces. Isabelle Kuhlmann. Joint Proceedings of the ECSQARU 2025 Workshops and Tutorials, 2025.

  5. Comparison of SAT-Based and ASP-Based Algorithms for Inconsistency Measurement. Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo, Matthias Thimm. Journal of Artificial Intelligence Research (JAIR), 82:563–685, 2025.

2024

  1. Inconsistency Measurement in LTLf Based on Minimal Inconsistent Sets and Minimal Correction Sets. Isabelle Kuhlmann, Carl Corea. Proceedings of the 16th International Conference on Scalable Uncertainty Management (SUM 2024), 2024.

  2. Increasing Interpretability in Outside Knowledge Visual Question Answering. Max Upravitelev, Christopher Krauss, Isabelle Kuhlmann. Proceedings of the 18th International Conference on Knowledge Management in Organizations (KMO 2024), 2024.

  3. Cluster-Specific Rule Mining for Argumentation-Based Classification. Jonas Klein, Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 1st International Conference on Recent Advances in Robust Argumentation Machines (RATIO 2024), 2024.

  4. Enhancing Abstract Argumentation Solvers with Machine Learning-Guided Heuristics: A Feasibility Study. Sandra Hoffmann, Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 1st International Conference on Recent Advances in Robust Argumentation Machines (RATIO 2024), 2024.

  5. Paraconsistent Reasoning for Inconsistency Measurement in Declarative Process Specifications. Carl Corea, Isabelle Kuhlmann, Matthias Thimm, John Grant. Information Systems 122, 2024.

2023

  1. Computing MUS-Based Inconsistency Measures. Isabelle Kuhlmann, Andreas Niskanen, Matti Järvisalo. Proceedings of the 18th European Conference on Logics in Artificial Intelligence (JELIA 2023), 2023.

  2. Non-Automata Based Conformance Checking of Declarative Process Specifications Based on ASP. Isabelle Kuhlmann, Carl Corea, John Grant. Proceedings of the 1st International Workshop on Formal Methods for Business Process Management (FMBPM 2023), 2023.

  3. An ASP-Based Framework for Solving Problems Related to Declarative Process Specifications. Isabelle Kuhlmann, Carl Corea, John Grant. Proceedings of the 21st International Workshop on Non-Monotonic Reasoning (NMR 2023), 2023.

  4. A Discussion of Challenges in Benchmark Generation for Abstract Argumentation. Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 1st International Workshop on Argumentation and Applications (Arg&App 2023), 2023.

  5. MaxSAT-Based Inconsistency Measurement. Andreas Niskanen, Isabelle Kuhlmann, Matthias Thimm, Matti Järvisalo. Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), 2023.

2022

  1. A Comparison of ASP-Based and SAT-Based Algorithms for the Contension Inconsistency Measure. Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo, Matthias Thimm. Proceedings of the 15th International Conference on Scalable Uncertainty Management (SUM 2022), 2022.

  2. On Bridging the Gap Between Machine Learning and Knowledge Representation and Reasoning: The Case of Abstract Argumentation. Isabelle Kuhlmann. Proceedings of the 1st International Conference on Foundations, Applications, and Theory of Inductive Logic (FATIL 2022), 2022.

  3. On the Impact of Data Selection when Applying Machine Learning in Abstract Argumentation. Isabelle Kuhlmann, Thorsten Wujek, Matthias Thimm. Proceedings of the 9th International Conference on Computational Models of Argument (COMMA 2022), 2022.

  4. Graph Neural Networks for Algorithm Selection in Abstract Argumentation. Jonas Klein, Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 1st International Workshop on Argumentation and Machine Learning (ArgML 2022), 2022.

2021

  1. Distinguishability in Abstract Argumentation. Isabelle Kuhlmann, Tjitze Rienstra, Lars Bengel, Kenneth Skiba, Matthias Thimm. Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning (KR 2021), 2021.

  2. Algorithms for Inconsistency Measurement using Answer Set Programming. Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 19th International Workshop on Non-Monotonic Reasoning (NMR 2021), 2021.

  3. Towards Eliciting Attacks in Abstract Argumentation Frameworks. Isabelle Kuhlmann. Online Handbook of Argumentation for AI, Volume 2, 2021.

  4. Integrating Feedforward Design into a Generative Network to Synthesize Supplementary Training Data for Object Classification. Isabelle Kuhlmann, Viktor Seib, Dietrich Paulus. Proceedings of the 2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC 2021), 2021.

2020

  1. An Algorithm for the Contension Inconsistency Measure Using Reductions to Answer Set Programming. Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 14th International Conference on Scalable Uncertainty Management (SUM 2020), 2020. Best Student Paper Award.

2019

  1. Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study. Isabelle Kuhlmann, Matthias Thimm. Proceedings of the 13th International Conference on Scalable Uncertainty Management (SUM 2019), 2019.

  2. Scratchy: A Lightweight Modular Autonomous Robot for Robotic Competitions. Raphael Memmesheimer, Isabelle Kuhlmann, Mark Mints, Patrik Schmidt, Christian Korbach, Ida Germann, Dietrich Paulus. Proceedings of the 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC 2019), 2019.