Lukas Vollenkemper
6 Publikationen
2024 | Artikel | FH-PUB-ID: 5470 |

Fischer, D., Hüsener, H. M., Grumbach, F., Vollenkemper, L., Müller, A., & Reusch, P. (2024). Demystifying Reinforcement Learning in Production Scheduling via Explainable AI. ArXiv. https://doi.org/10.48550/ARXIV.2408.09841
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2024 | Konferenzbeitrag | FH-PUB-ID: 4567
Grumbach, F., Müller, A., & Vollenkemper, L. (2024). Robust Human-Centered Assembly Line Scheduling with Reinforcement Learning. In M. Freitag, A. Kinra, H. Kotzab, & N. Megow (Eds.), Dynamics in Logistics. Proceedings of the 9th International Conference LDIC 2024, Bremen, Germany (pp. 223–234). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56826-8_17
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2023 | Artikel | FH-PUB-ID: 2855 |

Vollenkemper, L., Mönikes, M., Wortmann, F., Rudolph-Puls, M., Kohlhase, M., Röchter, A., & Ewering, C. (2023). HUMANZENTRIERTE PRODUKTIONSPLANUNG MIT KI - Entwicklung eines Assistenzsystems. Arbeitswelt.Plus Working Paper. https://doi.org/10.55594/UXIT4205
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2023 | Artikel | FH-PUB-ID: 2849 |

Vollenkemper, L., Grumbach, F., Kohlhase, M., & Reusch, P. (2023). Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops. Wt Werkstattstechnik Online, 113(04), 158–163. https://doi.org/10.37544/1436-4980-2023-04-58
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2022 | Artikel | FH-PUB-ID: 1799 |

Vandevoorde, K., Vollenkemper, L., Schwan, C., Kohlhase, M., & Schenck, W. (2022). Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks. Sensors, 22(7). https://doi.org/10.3390/s22072481
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2022 | Konferenzbeitrag | FH-PUB-ID: 2277 |

Vollenkemper, L., & Kohlhase, M. (2022). Spatial Temporal Transformer Networks for Sparse Motion Capture Applications. In H. Schulte, F. Hoffman, R. Mikut, & Karlsruhier Institut für Technologie (KIT) (Eds.), PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE (Vol. 32). Karlsruhe: KIT Scientific Publishing. https://doi.org/10.5445/KSP/1000151141
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6 Publikationen
2024 | Artikel | FH-PUB-ID: 5470 |

Fischer, D., Hüsener, H. M., Grumbach, F., Vollenkemper, L., Müller, A., & Reusch, P. (2024). Demystifying Reinforcement Learning in Production Scheduling via Explainable AI. ArXiv. https://doi.org/10.48550/ARXIV.2408.09841
HSBI-PUB
| DOI
| Download (ext.)
2024 | Konferenzbeitrag | FH-PUB-ID: 4567
Grumbach, F., Müller, A., & Vollenkemper, L. (2024). Robust Human-Centered Assembly Line Scheduling with Reinforcement Learning. In M. Freitag, A. Kinra, H. Kotzab, & N. Megow (Eds.), Dynamics in Logistics. Proceedings of the 9th International Conference LDIC 2024, Bremen, Germany (pp. 223–234). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56826-8_17
HSBI-PUB
| DOI
2023 | Artikel | FH-PUB-ID: 2855 |

Vollenkemper, L., Mönikes, M., Wortmann, F., Rudolph-Puls, M., Kohlhase, M., Röchter, A., & Ewering, C. (2023). HUMANZENTRIERTE PRODUKTIONSPLANUNG MIT KI - Entwicklung eines Assistenzsystems. Arbeitswelt.Plus Working Paper. https://doi.org/10.55594/UXIT4205
HSBI-PUB
| DOI
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2023 | Artikel | FH-PUB-ID: 2849 |

Vollenkemper, L., Grumbach, F., Kohlhase, M., & Reusch, P. (2023). Humanzentrierte Ablaufplanung von Montagelinien/Human-centered scheduling in assembly lines - Plug and play: Efficient algorithms minimize stress in flow shops. Wt Werkstattstechnik Online, 113(04), 158–163. https://doi.org/10.37544/1436-4980-2023-04-58
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2022 | Artikel | FH-PUB-ID: 1799 |

Vandevoorde, K., Vollenkemper, L., Schwan, C., Kohlhase, M., & Schenck, W. (2022). Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks. Sensors, 22(7). https://doi.org/10.3390/s22072481
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2022 | Konferenzbeitrag | FH-PUB-ID: 2277 |

Vollenkemper, L., & Kohlhase, M. (2022). Spatial Temporal Transformer Networks for Sparse Motion Capture Applications. In H. Schulte, F. Hoffman, R. Mikut, & Karlsruhier Institut für Technologie (KIT) (Eds.), PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE (Vol. 32). Karlsruhe: KIT Scientific Publishing. https://doi.org/10.5445/KSP/1000151141
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