| Classifying Metaheuristics: Towards a unified multi-level classification system H Stegherr, M Heider, J Hähner Natural Computing 21 (2), 155-171, 2022 | 81 | 2022 |
| A metaheuristic perspective on learning classifier systems M Heider, D Pätzel, H Stegherr, J Hähner Metaheuristics for Machine Learning: New Advances and Tools, 73-98, 2022 | 12 | 2022 |
| Separating rule discovery and global solution composition in a learning classifier system M Heider, H Stegherr, J Wurth, R Sraj, J Hähner Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 12 | 2022 |
| Learning classifier systems for self-explaining socio-technical-systems M Heider, H Stegherr, R Nordsieck, J Hähner arXiv preprint arXiv:2207.02300, 2022 | 12 | 2022 |
| Investigating the impact of independent rule fitnesses in a learning classifier system M Heider, H Stegherr, J Wurth, R Sraj, J Hähner International Conference on Bioinspired Optimization Methods and Their …, 2022 | 7 | 2022 |
| Comparing different metaheuristics for model selection in a supervised learning classifier system J Wurth, M Heider, H Stegherr, R Sraj, J Hähner Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 7 | 2022 |
| Assessing model requirements for explainable AI: A template and exemplary case study M Heider, H Stegherr, R Nordsieck, J Hähner Artificial Life 29 (4), 468-486, 2023 | 6 | 2023 |
| Analysing metaheuristic components H Stegherr, J Hähner | 6 | 2021 |
| Design of large-scale metaheuristic component studies H Stegherr, M Heider, L Luley, J Hähner Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 5 | 2021 |
| Metaheuristics for the minimum set cover problem: a comparison L Rosenbauer, A Stein, H Stegherr, J Hähner | 5 | 2020 |
| Approaches for rule discovery in a learning classifier system M Heider, H Stegherr, D Pätzel, R Sraj, J Wurth, B Volger, J Hähner | 4 | 2022 |
| Discovering rules for rule-based machine learning with the help of novelty search M Heider, H Stegherr, D Pätzel, R Sraj, J Wurth, B Volger, J Hähner SN Computer Science 4 (6), 778, 2023 | 3 | 2023 |
| SupRB in the context of rule-based machine learning methods: A comparative study M Heider, H Stegherr, R Sraj, D Pätzel, J Wurth, J Hähner Applied Soft Computing 147, 110706, 2023 | 2 | 2023 |
| Fast, Flexible, and Fearless: A Rust Framework for the Modular Construction of Metaheuristics J Wurth, H Stegherr, M Heider, L Luley, J Hähner Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023 | 2 | 2023 |
| A framework for modular construction and evaluation of metaheuristics H Stegherr, L Luley, J Wurth, M Heider, J Hähner | 2 | 2023 |
| Parallel Chemical Reaction Optimisation for the Utilisation in Intelligent RNA Prediction Systems H Stegherr, A Stein, J Hähner ARCS Workshop 2019; 32nd International Conference on Architecture of …, 2019 | 2 | 2019 |
| GRAHF: A Hyper-Heuristic Framework for Evolving Heterogeneous Island Model Topologies J Wurth, H Stegherr, M Heider, J Hähner Proceedings of the Genetic and Evolutionary Computation Conference, 1054-1063, 2024 | | 2024 |
| Assisting convergence behaviour characterisation with unsupervised clustering H Stegherr, M Heider, J Hähner | | 2023 |
| Suprb in the Context of Rule-Based Machine Learning M Heider, H Stegherr, R Sraj, D Pätzel, J Wurth, J Hähner Available at SSRN 4481895, 0 | | |
Jörg HähnerUniversität AugsburgVerified email at informatik.uni-augsburg.de
