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Deep Reinforcement Learning on Autonomous Driving Policy With Auxiliary Critic Network - IEEE Xplore
Deep reinforcement learning (DRL) is a machine learning method based on rewards, which can be extended to solve some complex and realistic decision-making problems. Autonomous driving needs to deal ...
The target enclosing control problem for autonomous vehicles with uncertainties necessitates simultaneous consideration of control optimality, robustness, and safety-guided performance constraints.
A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...
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