Trustworthy and explainable deep reinforcement learning for safe and energy-efficient process control: A use case in industrial compressed air systems
This paper presents a trustworthy reinforcement learning approach for the control of industrial compressed air systems. We develop a framework that enables safe and energy-efficient operation under realistic boundary conditions and introduce a multi-level explainability pipeline combining input pert...
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| Автори: | , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Elsevier
2026-05-01
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| Серія: | Energy and AI |
| Предмети: | |
| Онлайн доступ: | http://www.sciencedirect.com/science/article/pii/S266654682600011X |
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