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2020 – today
- 2024
[c10]Johannes Kühnel, Timo Eißmann, Christian Wiede, Dorothea Schwung, Anton Grabmaier:
Semi-Supervised Anomaly Detection in the TinyML Domain Through Multi-Target Few-Shot Domain Adaptation. ETFA 2024: 1-8- [i3]Steve Yuwono, Marlon Löppenberg, Dorothea Schwung, Andreas Schwung:
Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems. CoRR abs/2406.10015 (2024) - [i2]Steve Yuwono, Dorothea Schwung, Andreas Schwung:
Transfer learning of state-based potential games for process optimization in decentralized manufacturing systems. CoRR abs/2408.05992 (2024) - [i1]Steve Yuwono, Dorothea Schwung, Andreas Schwung:
Distributed Stackelberg Strategies in State-based Potential Games for Autonomous Decentralized Learning Manufacturing Systems. CoRR abs/2408.06397 (2024) - 2023
- [j4]Dorothea Schwung
, Steve Yuwono, Andreas Schwung, Steven X. Ding:
PLC-Informed Distributed Game Theoretic Learning of Energy-Optimal Production Policies. IEEE Trans. Cybern. 53(9): 5424-5435 (2023) - 2022
- [j3]Dorothea Schwung, Andreas Schwung, Steven X. Ding:
Distributed Self-Optimization of Modular Production Units: A State-Based Potential Game Approach. IEEE Trans. Cybern. 52(4): 2174-2185 (2022) - [c9]Steve Yuwono, Andreas Schwung, Dorothea Schwung:
The Impact of Communication and Memory in State-Based Potential Game-based Distributed Optimization. INDIN 2022: 335-340 - 2021
- [b1]Dorothea Schwung:
Maschinelle Lernalgorithmen zur Selbstoptimierung in verteilten Produktionssystemen basierend auf spieltheoretischen Konzepten. University of Duisburg-Essen, Germany, Shaker 2021, ISBN 978-3-8440-7840-4, pp. 1-148 - [j2]Dorothea Schwung, Steve Yuwono, Andreas Schwung, Steven X. Ding:
Decentralized learning of energy optimal production policies using PLC-informed reinforcement learning. Comput. Chem. Eng. 152: 107382 (2021)
2010 – 2019
- 2019
- [j1]Dorothea Schwung, Andreas Schwung, Steven X. Ding:
Actor-Critic Reinforcement Learning for Energy Optimization in Hybrid production Environments. Int. J. Comput. 18: 360-371 (2019) - [c8]Dorothea Schwung, Jan Niclas Reimann, Andreas Schwung, Steven X. Ding:
Potential Game based Distributed Optimization of Modular Production Units. INDIN 2019: 106-111 - [c7]Andreas Schwung, Dorothea Schwung, Mohammed Sharafath Abdul Hameed:
Cooperative Robot Control in Flexible Manufacturing Cells: Centralized vs. Distributed Approaches. INDIN 2019: 233-238 - [c6]Dorothea Schwung, Madhav Modali, Andreas Schwung:
Self-Optimization in Smart Production Systems using Distributed Reinforcement Learning. SMC 2019: 4063-4068 - 2018
- [c5]Dorothea Schwung, Jan Niclas Reimann, Andreas Schwung, Steven X. Ding:
Self Learning in Flexible Manufacturing Units: A Reinforcement Learning Approach. IEEE Conf. on Intelligent Systems 2018: 31-38 - [c4]Dorothea Schwung, Andreas Schwung, Steven X. Ding:
On-line Energy Optimization of Hybrid Production Systems Using Actor-Critic Reinforcement Learning. IEEE Conf. on Intelligent Systems 2018: 147-154 - 2017
- [c3]Andreas Schwung, Alexander Elbel, Dorothea Schwung:
System reconfiguration of modular production units using a SOA-based control structure. INDIN 2017: 121-126 - [c2]Dorothea Schwung, Fabian Csaplar, Andreas Schwung, Steven X. Ding:
An application of reinforcement learning algorithms to industrial multi-robot stations for cooperative handling operation. INDIN 2017: 194-199 - [c1]Dorothea Schwung, Tim Kempe, Andreas Schwung, Steven X. Ding:
Self-optimization of energy consumption in complex bulk good processes using reinforcement learning. INDIN 2017: 231-236
Coauthor Index
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