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2023
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Markus G?rlich-Bucher, Michael Heider, Tobias Ciemala and J?rg H?hner. 2023. A decision-theoretic approach for?prioritizing maintenance activities in?organic computing systems. Lecture Notes in Computer Science 13949, 37-47. DOI: 10.1007/978-3-031-42785-5_3
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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.
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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
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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
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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
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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
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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
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Neele Kemper, Michael Heider, Dirk Pietruschka and J?rg H?hner. in press. Forecasting of residential unit's heat demands: a comparison of machine learning techniques in a real-world case study. Enery Systems . DOI: 10.1007/s12667-023-00579-y
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Lukas Meitz, Michael Heider, Thorsten Sch?ler and J?rg H?hner. 2023. On data-preprocessing for effective predictive maintenance on multi-purpose machines. In Oleg Gusikhin, Slimane Hammoudi, Alfredo Cuzzocrea (Eds.). Proceedings of the 12th International Conference on Data Science, Technology and Applications, July 11-13, 2023, in Rome, Italy. SciTePress, Setúbal, 606-612 DOI: 10.5220/0012146700003541
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Markus G?rlich-Bucher, Michael Heider and J?rg H?hner. 2023. Predicting physical disturbances in?organic computing systems using automated machine learning. Lecture Notes in Computer Science 13949, 48-62. DOI: 10.1007/978-3-031-42785-5_4
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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
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David P?tzel, Michael Heider and J?rg H?hner. 2023. Towards principled synthetic benchmarks for explainable rule set learning algorithms. 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, 1657-1662 DOI: 10.1145/3583133.3596416
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Tobias Wittmeir, Michael Heider, André Schweiger, Michaela Kr?, J?rg H?hner, Johannes Schilp and Joachim Berlak. 2023. Towards robustness of production planning and control against supply chain disruptions. In David Herberger, Marco Hübner, Volker Stich (Eds.). Proceedings of the Conference on Production Systems and Logistics: CPSL 2023. publish-Ing., Hannover, 65-75 DOI: 10.15488/13425
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Henning Cui, Andreas Margraf, Michael Heider and J?rg H?hner. 2023. Towards understanding crossover for Cartesian Genetic Programming. In Niki van Stein, Francesco Marcelloni, H. K. Lam, Marie Cottrell, Joaquim Filipe (Eds.). Proceedings of the 15th International Joint Conference on Computational Intelligence - ECTA, November 13-15, 2023, in Rome, Italy. SciTePress, Setúbal, 308-314 DOI: 10.5220/0012231400003595
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2022
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Richard Nordsieck, Michael Heider, Anton Hummel and J?rg H?hner. 2022. A closer look at sum-based embeddings for knowledge graphs containing procedural knowledge. In Mehwish Alam, Davide Buscaldi, Michael Cochez, Francesco Osborne, Diego Reforgiato Recupero (Eds.). DL4KG 2022 - Deep Learning for Knowledge Graphs 2022: Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG 2022) co-located with the 21th International Semantic Web Conference (ISWC 2022), virtual conference, online, October 24, 2022. CEUR-WS, Aachen, 7
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Michael Heider, David P?tzel and Alexander R. M. Wagner. 2022. An overview of LCS research from 2021 to 2022. Proceedings of the Genetic and Evolutionary Computation Conference Companion 2086-2094. DOI: 10.1145/3520304.3533985
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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
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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
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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
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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
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Richard Nordsieck, Michael Heider, Alwin Hoffmann and J?rg H?hner. 2022. Reliability-based aggregation of heterogeneous knowledge to assist operators in manufacturing. 2022 IEEE 16th International Conference on Semantic Computing (ICSC) 131-138. DOI: 10.1109/icsc52841.2022.00027
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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
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Richard Nordsieck, Michael Heider, Anton Hummel, Alwin Hoffmann and J?rg H?hner. 2022. Towards models of conceptual and procedural operator knowledge. In Arild Waaler, Evgeny Kharlamov, Baifan Zhou, Dongzhuoran Zhou (Eds.). SemIIM 2022 - International Workshop on Semantic Industrial Information Modelling 2022: Proceedings of the First International Workshop on Semantic Industrial Information Modelling (SemIIM 2022) co-located with the 19th Extended Semantic Web Conference ESWC 2022, Greece, Crete, 30 May 2022. CEUR-WS, Aachen
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2021
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David P?tzel, Michael Heider and Alexander R. M. Wagner. 2021. An overview of LCS research from 2020 to 2021. 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, 1648-1656. DOI: 10.1145/3449726.3463173
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Andreas Wiedholz, Michael Heider, Richard Nordsieck, Andreas Angerer, Simon Dietrich and J?rg H?hner. 2021. CAD-based grasp and motion planning for process automation in fused deposition modelling. In Oleg Gusikhin, Henk Nijmeijer and Kurosh Madani (Ed.). Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics, July 6-8, 2021. SciTePress, Setúbal, 450-458. DOI: 10.5220/0010571204500458
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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
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Richard Nordsieck, Michael Heider, Anton Winschel and J?rg H?hner. 2021. Knowledge extraction via decentralized knowledge graph aggregation. In Dick Bulterman, Atsushi Kitazawa, David Ostrowski, Phillip Sheu and Jeffrey Tsai (Ed.). 2021 IEEE 15th International Conference on Semantic Computing (ICSC), 27-29 January 2021, Laguna Hills, CA, USA. IEEE, Piscataway, NJ, 92-99. DOI: 10.1109/icsc50631.2021.00024
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Michael Heider, Richard Nordsieck and J?rg H?hner. 2021. Learning classifier systems for self-explaining socio-technical-systems. In Anthony Stein, Sven Tomforde, Jean Botev, Peter Lewis (Eds.). 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
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2020
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Richard Nordsieck, Michael Heider, Andreas Angerer and J?rg H?hner. 2020. Evaluating the effect of user-given guiding attention on the learning process. In Esam El-Araby, Sven Tomforde, Timothy Wood, Pradeep Kumar, Claudia Raibulet, Ioan Petri, Gabriele Valentini, Phyllis Nelson and Barry Porter (Ed.). 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 17-21 August 2020, Washington, DC, USA. IEEE, Piscataway, NJ, 215-221. DOI: 10.1109/acsos49614.2020.00044
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Michael Heider, David P?tzel and J?rg H?hner. 2020. SupRB: a supervised rule-based learning system for continuous problems. preprint.
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Michael Heider, David P?tzel and J?rg H?hner. 2020. Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations. In Carlos Artemio Coello Coello (Ed.). Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (GECCO '20), Cancún, Mexico, July 2020. ACM, New York, NY, 127-128. DOI: 10.1145/3377929.3389963
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2019
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Michael Heider. 2019. Increasing reliability in FDM manufacturing. In C. Draude, M. Lange and B. Sick (Ed.). Informatik 2019: 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft (Workshop-Beitr?ge). Gesellschaft für Informatik e.V., Bonn, 483-491. DOI: 10.18420/inf2019_ws52
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Richard Nordsieck, Michael Heider, Andreas Angerer and J?rg H?hner. 2019. Towards automated parameter optimisation of machinery by persisting expert knowledge. In Oleg Gusikhin, Kurosh Madani and Janan Zaytoon (Ed.). Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics (ICINCO), July 29-31, 2019, Prague, Czech Republic. SciTePress, Setúbal, 406-413. DOI: 10.5220/0007953204060413
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2016
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Sebastian von Mammen, Heiko Hamann and Michael Heider. 2016. Robot gardens: an augmented reality prototype for plant-robot biohybrid systems. In Dieter Kranzlmüller and Gudrun Klinker (Ed.). Proceedings of the 22nd ACM Conference on Virtual Reality Software and Technology, VRST '16, Munich, Germany, November 2016. ACM, New York, NY, 139-142. DOI: 10.1145/2993369.2993400
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