Deep reinforcement learning on autonomous driving policy with auxiliary critic network

Y Wu, S Liao, X Liu, Z Li, R Lu - IEEE transactions on neural …, 2021 - ieeexplore.ieee.org
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 …
被引用次数：42 相关文章

Deep Reinforcement Learning on Autonomous Driving Policy With Auxiliary Critic Network.

Y Wu, S Liao, X Liu, Z Li, R Lu - IEEE Transactions on Neural …, 2021 - europepmc.org
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 …

Deep reinforcement learning on autonomous driving policy with auxiliary critic network

Y Wu, S Liao, X Liu, Z Li, R Lu - IEEE transactions on neural networks …, 2021 - safetylit.org
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 …

Deep Reinforcement Learning on Autonomous Driving Policy With Auxiliary Critic Network

Y Wu, S Liao, X Liu, Z Li, R Lu - IEEE transactions on …, 2023 - pubmed.ncbi.nlm.nih.gov
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 …

Deep reinforcement learning on autonomous driving policy with auxiliary critic network

Y Wu, S Liao, X Liu, Z Li, R Lu - IEEE transactions on neural networks …, 2021 - safetylit.org
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 …