Learning to Tune a Class of Controllers with Deep Reinforcement Learning
Control systems require maintenance in the form of tuning their parameters in order to maximize their performance in the face of process changes in minerals processing circuits. This work focuses on using deep reinforcement learning to train an agent to perform this maintenance continuously. A gener...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/11/9/989 |