Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives

arXiv:2404.00247v1 Announce Type: cross
Abstract: This paper provides insights into deep reinforcement learning (DRL) for process control from the perspective of transfer learning. We analyze the challenges of applying DRL in the field of process industries and the necessity of introducing transfer learning. Furthermore, recommendations and prospects are provided for future research directions on how transfer learning can be integrated with DRL to empower process control.

abstract analyze arxiv challenges control cs.ai cs.lg cs.sy eess.sy industries insights paper perspective perspectives process prospects recommendations reinforcement reinforcement learning transfer transfer learning type