A design methodology for deep reinforcement learning for autonomous Systems

M. Hillebrand, M. Lakhani, R. Dumitrescu, in: Procedia Manufacturing 52, 2020, pp. 266–271.

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Conference Paper | English
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Procedia Manufacturing 52
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52
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266-271
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Hillebrand M, Lakhani M, Dumitrescu R. A design methodology for deep reinforcement learning for autonomous Systems. In: Procedia Manufacturing 52. ; 2020:266-271. doi:https://doi.org/10.1016/j.promfg.2020.11.044
Hillebrand, M., Lakhani, M., & Dumitrescu, R. (2020). A design methodology for deep reinforcement learning for autonomous Systems. In Procedia Manufacturing 52 (pp. 266–271). https://doi.org/10.1016/j.promfg.2020.11.044
@inproceedings{Hillebrand_Lakhani_Dumitrescu_2020, title={A design methodology for deep reinforcement learning for autonomous Systems}, DOI={https://doi.org/10.1016/j.promfg.2020.11.044}, number={52}, booktitle={Procedia Manufacturing 52}, author={Hillebrand, Michael and Lakhani, Mohsin and Dumitrescu, Roman}, year={2020}, pages={266–271} }
Hillebrand, Michael, Mohsin Lakhani, and Roman Dumitrescu. “A Design Methodology for Deep Reinforcement Learning for Autonomous Systems.” In Procedia Manufacturing 52, 266–71, 2020. https://doi.org/10.1016/j.promfg.2020.11.044.
M. Hillebrand, M. Lakhani, and R. Dumitrescu, “A design methodology for deep reinforcement learning for autonomous Systems,” in Procedia Manufacturing 52, 2020, no. 52, pp. 266–271.
Hillebrand, Michael, et al. “A Design Methodology for Deep Reinforcement Learning for Autonomous Systems.” Procedia Manufacturing 52, no. 52, 2020, pp. 266–71, doi:https://doi.org/10.1016/j.promfg.2020.11.044.

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