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2020 – today
- 2024
[c6]David Heik, Alexander Böhm, Fouad Bahrpeyma, Dirk Reichelt
:
Application of Inhomogeneous QMIX in Various Architectures to Solve Dynamic Scheduling in Manufacturing Environments. INDIN 2024: 1-8- 2023
- [j1]Pia Bielitz, Nicole Jäpel, David Heik, Dirk Reichelt:
Ganzheitliche Wandlungsfähigkeit von Produktionssystemen - der Schlüssel zur Ressourcenwende? HMD Prax. Wirtsch. 60(6): 1222-1236 (2023) - [c5]David Heik, Fouad Bahrpeyma, Dirk Reichelt:
Solving a Dynamic Scheduling Problem for a Manufacturing System with Reinforcement Learning. IntelliSys (2) 2023: 413-432 - [c4]David Heik, Fouad Bahrpeyma, Dirk Reichelt:
Application of Multi-agent Reinforcement Learning to the Dynamic Scheduling Problem in Manufacturing Systems. LOD (2) 2023: 237-254 - 2022
- [c3]David Heik, Fouad Bahrpeyma, Dirk Reichelt:
An Application of Reinforcement Learning in Industrial Cyber-Physical Systems. OVERLAY@AI*IA 2022: 51-55 - [c2]David Heik, Fouad Bahrpeyma, Dirk Reichelt:
Dynamic Job Shop Scheduling in an Industrial Assembly Environment Using Various Reinforcement Learning Techniques. ISDA (3) 2022: 523-533 - 2020
- [c1]David Heik, Javad Ghofrani, Dirk Reichelt:
Adaptive Management Shell for Mapping the Process Capability of Manufacturing Components: A Systematic Mapping Study. INDIN 2020: 7-14
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