Application of Multi-agent Reinforcement Learning to the Dynamic Scheduling Problem in Manufacturing Systems
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53966-4_18
Reference31 articles.
1. Alqoud, A., Schaefer, D., Milisavljevic-Syed, J.: Industry 4.0: a systematic review of legacy manufacturing system digital retrofitting. Manuf. Rev. 9, 32 (2022). https://doi.org/10.1051/mfreview/2022031
2. Bahrpeyma, F., Haghighi, H., Zakerolhosseini, A.: An adaptive rl based approach for dynamic resource provisioning in cloud virtualized data centers. Computing 97, 1209–1234 (2015)
3. Bahrpeyma, F., Zakerolhoseini, A., Haghighi, H.: Using ids fitted q to develop a real-time adaptive controller for dynamic resource provisioning in cloud’s virtualized environment. Appl. Soft Comput. 26, 285–298 (2015)
4. Burggräf, P., Wagner, J., Saßmannshausen, T., Ohrndorf, D., Subramani, K.: Multi-agent-based deep reinforcement learning for dynamic flexible job shop scheduling. Procedia CIRP 112, 57–62 (2022). https://doi.org/10.1016/j.procir.2022.09.024
5. Carroll, D.C.: Heuristic sequencing of single and multiple component jobs. Ph.D. thesis, Massachusetts Institute of Technology (1965)
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