| Modular augmented reality platform for smart operator in production environment J Um, J Popper, M Ruskowski 2018 IEEE Industrial Cyber-Physical Systems (ICPS), 720-725, 2018 | 26 | 2018 |
| Simultaneous production and agv scheduling using multi-agent deep reinforcement learning J Popper, V Yfantis, M Ruskowski Procedia Cirp 104, 1523-1528, 2021 | 17 | 2021 |
| Production bots für production level 4: skill-basierte systeme für die produktion der zukunft M Ruskowski, A Herget, J Hermann, W Motsch, P Pahlevannejad, ... atp magazin 62 (9), 62-71, 2020 | 16 | 2020 |
| Enabling a multi-agent system for resilient production flow in modular production systems S Komesker, W Motsch, J Popper, A Sidorenko, A Wagner, M Ruskowski Procedia CIRP 107, 991-998, 2022 | 13 | 2022 |
| Utilizing multi-agent deep reinforcement learning for flexible job shop scheduling under sustainable viewpoints J Popper, W Motsch, A David, T Petzsche, M Ruskowski 2021 International Conference on Electrical, Computer, Communications and …, 2021 | 12 | 2021 |
| Using multi-agent deep reinforcement learning for flexible job shop scheduling problems J Popper, M Ruskowski Procedia CIRP 112, 63-67, 2022 | 8 | 2022 |
| Method for the development of an asset administration shell in a product-driven modular production–realizing an active digital object memory M Birtel, W Motsch, J Popper, M Ruskowski 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS) 1, 583-588, 2020 | 8 | 2020 |
| Artificial intelligence across industries J Popper, J Hermann, K Cui, S Bergweiler, S Weyer, M Ruskowski, ... | 6 | 2018 |
| Enabling reliable visual quality control in smart factories through TSN J Popper, C Harms, M Ruskowski Procedia CIRP 88, 549-553, 2020 | 5 | 2020 |
| Vorgehensweise zum Retrofitting einer Stanzmaschine zur Visualisierung von Prozessdaten M Birtel, J Popper Gesellschaft für Informatik eV, 2018 | 4 | 2018 |
| Reinforcement Learning-based Scheduling of a Job-Shop Process with Distributedly Controlled Robotic Manipulators for Transport Operations S Jungbluth, N Gafur, J Popper, V Yfantis, M Ruskowski IFAC-PapersOnLine 55 (2), 156-162, 2022 | 3 | 2022 |
| Decentralized Holistic Production Scheduling with Multi-agent Deep Reinforcement Learning J Popper VDI Verlag GmbH, 2023 | | 2023 |
| 模块化机器的安全白皮书 J Popper, M BLugel, H Burchardt, S Horn, J Merx, D Richter, W Varro, ... 仪器仪表标准化与计量 4, 2019 | | 2019 |
