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超全！深度強化學(xué)習(xí)領(lǐng)域值得一讀的論文列表
參考自：https://spinningup.openai.com/en/latest/spinningup/keypapers.html[ht...
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[TRPO] Trust Region Policy Optimization論文鏈接：http://proceedings.mlr.press/v37/schulman15[http://proceedings.mlr....
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[DDPG] Continuous Control with Deep Reinforcement Learning論文鏈接：https://arxiv.org/abs/1509.02971[https://arxiv.org/abs/1509.02971]引...
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[DQN] Playing Atari with Deep Reinforcement Learning論文鏈接：https://arxiv.org/abs/1312.5602[https://arxiv.org/abs/1312.5602]引用：...
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[Chapter 6] Reinforcement Learning (4) Policy Search
In the previous sections, we try to learn the utility function, or more ...
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[Chapter 5] Reinforcement Learning (3) Function Approximation and Going Deep
Function Approximation While we are learning the Q-functions, but how to...
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[Chapter 4] Reinforcement Learning (2) Model-Free Method
Model-Free RL Method In model-based method, we need firstly model the en...
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[Chapter 3] Reinforcement Learning (1) Model-Based Method
Reinforcement Learning Firstly, we assume that all the environments in t...
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[Chapter 2] Value Iteration and Policy Iteration
We now know the most important thing for computing an optimal policy is ...