David Pätzel
Title
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Cited by
Year
A survey of formal theoretical advances regarding XCS
D Pätzel, A Stein, J Hähner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019
172019
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
62020
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
52020
An algebraic description of XCS
D Pätzel, J Hähner
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
52018
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
42020
XCSF for automatic test case prioritization
L Rosenbauer, A Stein, D Pätzel, J Hähner
42020
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
32020
Transfer learning for automated test case prioritization using XCSF
L Rosenbauer, D Pätzel, A Stein, J Hähner
International Conference on the Applications of Evolutionary Computation …, 2021
22021
SupRB: A Supervised Rule-based Learning System for Continuous Problems
M Heider, D Pätzel, J Hähner
arXiv preprint arXiv:2002.10295, 2020
22020
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
2021
An Organic Computing System for Automated Testing
L Rosenbauer, D Pätzel, A Stein, J Hähner
International Conference on Architecture of Computing Systems, 135-149, 2021
2021
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Articles 1–11