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eess.SY2021
Recurrent Model Predictive Control
Zhengyu Liu, Jingliang Duan, Wenxuan Wang +5
This paper proposes an off-line algorithm, called Recurrent Model Predictive Control (RMPC), to solve general nonlinear finite-horizon optimal control problems. Unlike traditional…
eess.SY2020
Mixed Reinforcement Learning with Additive Stochastic Uncertainty
Yao Mu, Shengbo Eben Li, Chang Liu +4
Reinforcement learning (RL) methods often rely on massive exploration data to search optimal policies, and suffer from poor sampling efficiency. This paper presents a mixed reinfor…