Reliable and Accurate Autonomous Flow Operation based on Off-line Trained Reinforcement Learning

A RL agent trained offline for reliability and able to refine its policies during online operation is proposed. Results for three illustrative flow automation use cases show remarkable performance with extraordinary adaptability to changes.