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PC-Gym is an open-source tool for developing and evaluating reinforcement learning (RL) algorithms in chemical process control.
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Richard. Sutton and Andrew. Barto · 2018
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John Schulman et al · 2018
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“Reinforcement Learning – Overview of recent progress and implications for process control”
Joohyun Shin, Thomas. Badgwell, Kuang-Hung Liu and Jay. Lee · 2019
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“Where Reinforcement Learning Meets Process Control: Review and Guidelines”
Ruan Faria, Bruno Capron, Argimiro Secchi and Maurício. De · 2022
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“Chance constrained policy optimization for process control and optimization”
Panagiotis Petsagkourakis et al · 2022
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“Deep reinforcement learning with shallow controllers: An experimental application to PID tuning”
Nathan Lawrence et al · 2022
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“gymnax: A JAX-based Reinforcement Learning Environment Library”, 2022
Robert Lange · 2022
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“Chance constrained policy optimization for process control and optimization”
Panagiotis Petsagkourakis et al · 2022
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“A review On reinforcement learning: Introduction and applications in industrial process control”
Rui Nian, Jinfeng Liu and Biao Huang · 2020
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Lingwei Zhu et al · 2020
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Yiming Zhang, Quan Vuong and Keith Ross · 2020
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“Safe chance constrained reinforcement learning for batch process control”
Max Mowbray, Panagiotis Petsagkourakis, Ehecatl del Rio-Chanona and Dongda Zhang · 2022
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