2023
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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, 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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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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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 BibTeX | RIS | DOI
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Henning Cui, David P?tzel, Andreas Margraf and J?rg H?hner. 2023. Weighted mutation of connections to mitigate search space limitations in Cartesian Genetic Programming. In FOGA '23: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 30 August - 1 September 2023, Potsdam, Germany. Association for Computing Machinery, New York, NY, 50-60 DOI: 10.1145/3594805.3607130 PDF | BibTeX | RIS | DOI
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2022
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Lukas Rosenbauer, David P?tzel, Anthony Stein and J?rg H?hner. 2022. A learning classifier system for automated test case prioritization and selection. SN Computer Science 3, 5, 373. DOI: 10.1007/s42979-022-01255-1 BibTeX | RIS | DOI
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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 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. 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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David P?tzel and J?rg H?hner. 2022. The Bayesian learning classifier system: implementation, replicability, comparison with XCSF. In Jonathan E. Fieldsend, Markus Wagner (Eds.). GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, July 9-13, 2022, Boston, MA, USA. ACM, New York, NY, 413-421 DOI: 10.1145/3512290.3528736 BibTeX | RIS | DOI
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2021
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Lukas Rosenbauer, David P?tzel, Anthony Stein and J?rg H?hner. 2021. An organic computing system for?automated testing. In Christian Hochberger, Lars Bauer and Thilo Pionteck (Ed.). Architecture of computing systems. Springer International Publishing, Cham (LNTCS ; 12800), 135-149. DOI: 10.1007/978-3-030-81682-7_9 BibTeX | RIS | DOI
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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 PDF | BibTeX | RIS | DOI
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Lukas Rosenbauer, David P?tzel, Anthony Stein and J?rg H?hner. 2021. Transfer learning for automated test case prioritization using XCSF. In Applications of Evolutionary Computation: EvoApplications 2021. Springer, Cham, 681-696 DOI: 10.1007/978-3-030-72699-7_43 BibTeX | RIS | DOI | URL
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2020
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David P?tzel, Anthony Stein and Masaya Nakata. 2020. An overview of LCS research from IWLCS 2019 to 2020. In Carlos Artemio Coello Coello (Ed.). Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (GECCO '20), July 2020, Cancún, Mexico. ACM, New York, NY, 1782-1788. DOI: 10.1145/3377929.3398105 BibTeX | RIS | DOI
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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. BibTeX | RIS | URL
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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 PDF | BibTeX | RIS | DOI
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Lukas Rosenbauer, Anthony Stein, Roland Maier, David P?tzel and J?rg H?hner. 2020. XCS as a reinforcement learning approach to automatic test case prioritization. In Carlos Artemio Coello Coello (Ed.). Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, Cancún, Mexico, July, 2020. ACM, New York, NY, 1798-1806. DOI: 10.1145/3377929.3398128 BibTeX | RIS | DOI
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Lukas Rosenbauer, Anthony Stein, David P?tzel and J?rg H?hner. 2020. XCSF for automatic test case prioritization. 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, 49-58. DOI: 10.5220/0010105700490058 PDF | BibTeX | RIS | DOI
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Lukas Rosenbauer, Anthony Stein, David P?tzel and J?rg H?hner. 2020. XCSF with experience replay for automatic test case prioritization. In Hussein Abbass, Carlos A. Coello Coello and Hemant Kumar Singh (Ed.). 2020 IEEE Symposium Series on Computational Intelligence (SSCI), virtual event, Canberra, Australia, 1-4 December 2020. IEEE, Piscataway, NJ, 1307-1314. DOI: 10.1109/ssci47803.2020.9308379 BibTeX | RIS | DOI
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2019
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David P?tzel, Anthony Stein and J?rg H?hner. 2019. A survey of formal theoretical advances regarding XCS. In Manuel López-Ibá?ez, Anne Auger and Thomas Stützle (Ed.). Proceedings of the Genetic and Evolutionary Computation Conference Companion - GECCO '19, Prague, Czech Republic, July 2019. ACM Press, New York, NY, 1295-1302. DOI: 10.1145/3319619.3326848 BibTeX | RIS | DOI
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2018
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David P?tzel and J?rg H?hner. 2018. An algebraic description of XCS. In Hernan Aguirre and Keiki Takadama (Ed.). Proceedings of the Genetic and Evolutionary Computation Conference Companion - GECCO '18, Kyoto, Japan — July 15 - 19, 2018. ACM Press, New York, NY, 1434-1441. DOI: 10.1145/3205651.3208248 BibTeX | RIS | DOI
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