Seuraa
David Pätzel
David Pätzel
Universität Augsburg
Vahvistettu sähköpostiosoite verkkotunnuksessa uni-a.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
A survey of formal theoretical advances regarding XCS
D Pätzel, A Stein, J Hähner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
232019
XCS as a reinforcement learning approach to automatic test case prioritization
L Rosenbauer, A Stein, R Maier, D Pätzel, J Hähner
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
182020
XCSF with Experience Replay for Automatic Test Case Prioritization
L Rosenbauer, A Stein, D Pätzel, J Hähner
2020 IEEE Symposium Series on Computational Intelligence (SSCI), 1307-1314, 2020
162020
An overview of LCS research from IWLCS 2019 to 2020
D Pätzel, A Stein, M Nakata
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
142020
Transfer learning for automated test case prioritization using XCSF
L Rosenbauer, D Pätzel, A Stein, J Hähner
Applications of Evolutionary Computation: 24th International Conference …, 2021
92021
An overview of LCS research from 2020 to 2021
D Pätzel, M Heider, ARM Wagner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021
72021
Towards a Pittsburgh-style LCS for learning manufacturing machinery parametrizations
M Heider, D Pätzel, J Hähner
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
62020
An algebraic description of XCS
D Pätzel, J Hähner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
62018
XCSF for automatic test case prioritization
L Rosenbauer, A Stein, D Pätzel, J Hähner
52020
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
42022
An overview of LCS research from 2021 to 2022
M Heider, D Pätzel, ARM Wagner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022
32022
Approaches for Rule Discovery in a Learning Classifier System
M Heider, H Stegherr, D Pätzel, R Sraj, J Wurth, B Volger, J Hähner
14th International Joint Conference on Computational Intelligence - ECTA, 39–49, 2022
32022
An organic computing system for automated testing
L Rosenbauer, D Pätzel, A Stein, J Hähner
Architecture of Computing Systems: 34th International Conference, ARCS 2021 …, 2021
32021
A learning classifier system for automated test case prioritization and selection
L Rosenbauer, D Pätzel, A Stein, J Hähner
SN Computer Science 3 (5), 373, 2022
22022
SupRB: A Supervised Rule-based Learning System for Continuous Problems
M Heider, D Pätzel, J Hähner
arXiv preprint arXiv:2002.10295, 2020
22020
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
12023
Weighted Mutation of Connections To Mitigate Search Space Limitations in Cartesian Genetic Programming
H Cui, D Pätzel, A Margraf, J Hähner
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic …, 2023
12023
Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms
D Pätzel, M Heider, J Hähner
Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023
12023
Deep Q-Network Updates for the Full Action-Space Utilizing Synthetic Experiences
WP von Pilchau, D Pätzel, A Stein, J Hähner
2023 International Joint Conference on Neural Networks (IJCNN), 1-9, 2023
12023
Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners
D Pätzel, R Nordsieck, J Hähner
International Conference on the Applications of Evolutionary Computation …, 2024
2024
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Artikkelit 1–20