3 citations · 8 across the 8 of their papers we have counts for
9 papers
Variance Reduction Based Experience Replay for Policy Optimization
Hua Zheng, Wei Xie, M. Ben Feng +1
Effective reinforcement learning (RL) for complex stochastic systems requires leveraging historical data to improve sample efficiency and accelerate policy optimization. However, c…
Digital Twin Calibration with Model-Based Reinforcement Learning
Hua Zheng, Wei Xie, Ilya O. Ryzhov +1
This paper presents a novel methodological framework, called the Actor-Simulator, that incorporates the calibration of digital twins into model-based reinforcement learning for mor…
Digital Twin Calibration for Biological System-of-Systems: Cell Culture Manufacturing Process
Fuqiang Cheng, Wei Xie, Hua Zheng
Biomanufacturing innovation relies on an efficient Design of Experiments (DoEs) to optimize processes and product quality. Traditional DoE methods, ignoring the underlying bioproce…
Variance Reduction based Experience Replay for Policy Optimization
Hua Zheng, Wei Xie, M. Ben Feng
For reinforcement learning on complex stochastic systems where many factors dynamically impact the output trajectories, it is desirable to effectively leverage the information from…
Opportunities of Hybrid Model-based Reinforcement Learning for Cell Therapy Manufacturing Process Control
Hua Zheng, Wei Xie, Keqi Wang +1
Driven by the key challenges of cell therapy manufacturing, including high complexity, high uncertainty, and very limited process observations, we propose a hybrid model-based rein…
Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care
Hua Zheng, Jiahao Zhu, Wei Xie +1
Patients with severe Coronavirus disease 19 (COVID-19) typically require supplemental oxygen as an essential treatment. We developed a machine learning algorithm, based on a deep R…