… Kurtulus, “Enhancing situational awareness and performance of adaptive cruise control
through model predictive control and deep reinforcement learning,” in 2019 IEEE Intelligent …

… Pinto, “Robust tube-based model predictive control for lateral path tracking,” IEEE … , “Comparison
of deep reinforcement learning and model predictive control for adaptive cruise control,” …

… Despite that the basic idea of this work is closely related to some model-based RL algorithm
combined with model predictive control [17-19], the way of the guidance proposed in this …

… work is to compare the performance of model predictive and deep reinforcement learning
control strategies. Considering that both control techniques benefit from predictions of future …

… case study, we show that a twin delayed deep deterministic policy gradient (TD3) RL agent
offers … We conclude that reinforcement learning is a viable optimal control technique for multi-…

… to find optimal control signals while handling constraints in a principled way. We propose
probabilistic model predictive control (MPC) with learned GP models, while propagating …

… The model predictive control (MPC) achieves this aim by optimizing a cumulative objective
… a deep reinforcement learning (DRL) algorithm for HVAC control based on the deep Q-…

… industrial fields including process control. In this paper, we propose a novel approach for
model predictive control (MPC) combined with deep reinforcement learning (DRL) technology. …

… in the muscle control . In the first part, we used model predictive control to obtain energy …
The second part is to use deep reinforcement learning to obtain a sequence of stimulus to …

… The control performance of reinforcement learning (RL) and model predictive control (MPC) …
However, in existing studies, the reinforcement learning and model predictive control are …