An application of reinforcement learning algorithms to industrial multi-robot stations for cooperative handling operation. - Dorothea Schwung; Fabian Csaplar; Andreas Schwung; Steven X. Ding (INDIN, 2017)

System reconfiguration of modular production units using a SOA-based control structure. - Andreas Schwung; Alexander Elbel; Dorothea Schwung (INDIN, 2017)

Self-optimization of energy consumption in complex bulk good processes using reinforcement learning. - Dorothea Schwung; Tim Kempe; Andreas Schwung; Steven X. Ding (INDIN, 2017)

Self Learning in Flexible Manufacturing Units: A Reinforcement Learning Approach. - Dorothea Schwung; Jan Niclas Reimann; Andreas Schwung; Steven X. Ding (IEEE Conf. on Intelligent Systems, 2018)

On-line Energy Optimization of Hybrid Production Systems Using Actor-Critic Reinforcement Learning. - Dorothea Schwung; Andreas Schwung; Steven X. Ding (IEEE Conf. on Intelligent Systems, 2018)

Potential Game based Distributed Optimization of Modular Production Units. - Dorothea Schwung; Jan Niclas Reimann; Andreas Schwung; Steven X. Ding (INDIN, 2019)

Cooperative Robot Control in Flexible Manufacturing Cells: Centralized vs. Distributed Approaches. - Andreas Schwung; Dorothea Schwung; Mohammed Sharafath Abdul Hameed (INDIN, 2019)

Self-Optimization in Smart Production Systems using Distributed Reinforcement Learning. - Dorothea Schwung; Madhav Modali; Andreas Schwung (SMC, 2019)

Actor-Critic Reinforcement Learning for Energy Optimization in Hybrid production Environments. - Dorothea Schwung; Andreas Schwung; Steven X. Ding (Int. J. Comput., 2019)

Decentralized learning of energy optimal production policies using PLC-informed reinforcement learning. - Dorothea Schwung; Steve Yuwono; Andreas Schwung; Steven X. Ding (Comput. Chem. Eng., 2021)

Maschinelle Lernalgorithmen zur Selbstoptimierung in verteilten Produktionssystemen basierend auf spieltheoretischen Konzepten. - Dorothea Schwung (Shaker, 2021)

The Impact of Communication and Memory in State-Based Potential Game-based Distributed Optimization. - Steve Yuwono; Andreas Schwung; Dorothea Schwung (INDIN, 2022)

Distributed Self-Optimization of Modular Production Units: A State-Based Potential Game Approach. - Dorothea Schwung; Andreas Schwung; Steven X. Ding (IEEE Trans. Cybern., 2022)

PLC-Informed Distributed Game Theoretic Learning of Energy-Optimal Production Policies. - Dorothea Schwung; Steve Yuwono; Andreas Schwung; Steven X. Ding (IEEE Trans. Cybern., 2023)

Model-based Reinforcement Learning for Sim-to-Real Transfer in Robotics using HTM neural networks. - Rizky M. Diprasetya; Ali Nafih Pullani; Andreas Schwung; Dorothea Schwung (CoDIT, 2024)

Semi-Supervised Anomaly Detection in the TinyML Domain Through Multi-Target Few-Shot Domain Adaptation. - Johannes Kühnel; Timo Eißmann; Christian Wiede; Dorothea Schwung; Anton Grabmaier (ETFA, 2024)

Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems. - Steve Yuwono; Marlon Löppenberg; Dorothea Schwung; Andreas Schwung (IECON, 2024)

Transfer learning of state-based potential games for process optimization in decentralized manufacturing systems. - Steve Yuwono; Dorothea Schwung; Andreas Schwung (CoRR, 2024)

Distributed Stackelberg Strategies in State-based Potential Games for Autonomous Decentralized Learning Manufacturing Systems. - Steve Yuwono; Dorothea Schwung; Andreas Schwung (CoRR, 2024)

Self-optimization in distributed manufacturing systems using Modular State-based Stackelberg Games. - Steve Yuwono; Ahmar Kamal Hussain; Dorothea Schwung; Andreas Schwung (CoRR, 2024)

Real Time Self-Tuning Adaptive Controllers on Temperature Control Loops using Event-based Game Theory. - Steve Yuwono; Muhammad Uzair Rana; Dorothea Schwung; Andreas Schwung (CoRR, 2025)