2023
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Helena Stegherr, Leopold Luley, Jonathan Wurth, Michael Heider and J?rg H?hner. 2023. A framework for modular construction and evaluation of metaheuristics. Reports / Technische Berichte der Fakult?t für Angewandte Informatik der Universit?t Augsburg 2023-01. Institut für Informatik, Universit?t Augsburg, Augsburg. PDF | BibTeX | RIS
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Michael Heider, David P?tzel, Helena Stegherr and J?rg H?hner. 2023. A metaheuristic perspective on learning classifier systems. In Mansour Eddaly, Bassem Jarboui and Patrick Siarry (Ed.). Metaheuristics for machine learning: new advances and tools. Springer, Singapore (Computational Intelligence Methods and Applications (CIMA)), 73-98. DOI: 10.1007/978-981-19-3888-7_3 PDF | BibTeX | RIS | DOI
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Michael Heider, Helena Stegherr, Richard Nordsieck and J?rg H?hner. 2023. Assessing model requirements for explainable AI: a template and exemplary case study. Artificial Life 29, 4, 468-486. DOI: 10.1162/artl_a_00414 PDF | BibTeX | RIS | DOI
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Helena Stegherr, Michael Heider and J?rg H?hner. 2023. Assisting convergence behaviour characterisation with unsupervised clustering. In Niki van Stein, Francesco Marcelloni, H. K. Lam, Marie Cottrell, Joaquim Filipe (Eds.). Proceedings of the 15th International Joint Conference on Computational Intelligence, November 13-15, 2023, in Rome, Italy. SciTePress, Setúbal, 108-118 DOI: 10.5220/0012202100003595 PDF | BibTeX | RIS | DOI
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Michael Heider, Helena Stegherr, David P?tzel, Roman Sraj, Jonathan Wurth, Benedikt Volger and J?rg H?hner. 2023. Discovering rules for rule-based machine learning with the help of novelty search. SN Computer Science 4, 6, 778. DOI: 10.1007/s42979-023-02198-x PDF | BibTeX | RIS | DOI
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Jonathan Wurth, Helena Stegherr, Michael Heider, Leopold Luley and J?rg H?hner. 2023. Fast, flexible, and fearless: a rust framework for the modular construction of metaheuristics. In Sara Silva, Luís Paquete (Eds.). GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, Lisbon, Portugal, July 15-19, 2023. ACM, New York, NY, 1900-1909 DOI: 10.1145/3583133.3596335 BibTeX | RIS | DOI
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Michael Heider, Helena Stegherr, Roman Sraj, David P?tzel, Jonathan Wurth and J?rg H?hner. 2023. SupRB in the context of rule-based machine learning methods: a comparative study. Applied Soft Computing 147, 110706. DOI: 10.1016/j.asoc.2023.110706 BibTeX | RIS | DOI
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2022
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Michael Heider, Helena Stegherr, David P?tzel, Roman Sraj, Jonathan Wurth, Benedikt Volger and J?rg H?hner. 2022. Approaches for rule discovery in a learning classifier system. In Thomas B?ck, Bas van Stein, Christian Wagner, Jonathan Garibaldi, H. K. Lam, Marie Cottrell, Faiyaz Doctor, Joaquim Filipe, Kevin Warwick, Janusz Kacprzyk (Eds.). Proceedings of the 14th International Joint Conference on Computational Intelligence, October 24-26, 2022, in Valletta, Malta. SciTePress, Setúbal, 39-49 DOI: 10.5220/0011542000003332 PDF | BibTeX | RIS | DOI
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Helena Stegherr, Michael Heider and J?rg H?hner. 2022. Classifying metaheuristics: towards a unified multi-level classification system. Natural Computing 21, 155-171. DOI: 10.1007/s11047-020-09824-0 PDF | BibTeX | RIS | DOI
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Jonathan Wurth, Michael Heider, Helena Stegherr, Roman Sraj and J?rg H?hner. 2022. Comparing different metaheuristics for model selection in a supervised learning classifier system. Proceedings of the Genetic and Evolutionary Computation Conference Companion 316-319. DOI: 10.1145/3520304.3529015 PDF | BibTeX | RIS | DOI
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Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj and J?rg H?hner. 2022. Investigating the?impact of?independent rule fitnesses in?a?learning classifier system. Lecture Notes in Computer Science 13627, 142-156. DOI: 10.1007/978-3-031-21094-5_11 PDF | BibTeX | RIS | DOI
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Michael Heider, Helena Stegherr, Jonathan Wurth, Roman Sraj and J?rg H?hner. 2022. Separating rule discovery and global solution composition in a learning classifier system. Proceedings of the Genetic and Evolutionary Computation Conference Companion 248-251. DOI: 10.1145/3520304.3529014 PDF | BibTeX | RIS | DOI
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2021
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Helena Stegherr and J?rg H?hner. 2021. Analysing metaheuristic components. In Anthony Stein, Sven Tomforde, Jean Botev and Peter Lewis (Ed.). LIFELIKE 2020 & LIFELIKE 2021, Lifelike Computing Systems Workshop 2020 and 2021: Joint Proceedings of the LIFELIKE 2020 - 8th Edition in the Evolution of the Workshop Series of Autonomously Learning and Optimizing Systems (SAOS) co-located with 2020 Conference on Artificial Life (ALIFE 2020), Online, July 16th, 2020, and the LIFELIKE 2021 - 9th Edition in the Evolution of the Workshop Series of Autonomously Learning and Optimizing Systems (SAOS) co-located with 2021 Conference on Artificial Life (ALIFE 2021), Online, July 19th, 2021. CEUR-WS (CEUR Workshop Proceedings ; Vol-3007) PDF | BibTeX | RIS | URL
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Helena Stegherr, Michael Heider, Leopold Luley and J?rg H?hner. 2021. Design of large-scale metaheuristic component studies. In Francisco Chicano and Krzysztof Krawiec (Ed.). Proceedings of the Genetic and Evolutionary Computation Conference Companion, Lille, France, July 10 - 14, 2021. ACM, New York, NY, 1217-1226. DOI: 10.1145/3449726.3463168 PDF | BibTeX | RIS | DOI
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2020
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Lukas Rosenbauer, Anthony Stein, Helena Stegherr and J?rg H?hner. 2020. Metaheuristics for the minimum set cover problem: a comparison. In Juan Julian Merelo, Jonathan Garibaldi, Christian Wagner, Thomas B?ck, Kurosh Madani and Kevin Warwick (Ed.). Proceedings of the 12th International Joint Conference on Computational Intelligence (ECTA), November 2-4, 2020. SciTePress, Setúbal, 123-130. DOI: 10.5220/0010019901230130 PDF | BibTeX | RIS | DOI
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2019
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Helena Stegherr, Anthony Stein and J?rg H?hner. 2019. Parallel chemical reaction optimization for utilization in intelligent RNA prediction systems. In Carsten Trinitis, Thilo Pionteck (Eds.). Intelligent Systems Workshop, part of ARCS 2019: 32nd International Conference on Architecture of Computing Systems; workshop proceedings; May 20- 21, 2019, Technical 新万博体育下载_万博体育app【投注官网】 of Denmark, Copenhagen, Denmark. VDE Verlag, Berlin, 135-142 PDF | BibTeX | RIS | URL
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