发简信
IP属地：山西
-
超全！深度强化学习领域值得一读的论文列表
参考自：https://spinningup.openai.com/en/latest/spinningup/keypapers.html[ht...
-
[TRPO] Trust Region Policy Optimization论文链接：http://proceedings.mlr.press/v37/schulman15[http://proceedings.mlr....
-
[DDPG] Continuous Control with Deep Reinforcement Learning论文链接：https://arxiv.org/abs/1509.02971[https://arxiv.org/abs/1509.02971]引...
-
[DQN] Playing Atari with Deep Reinforcement Learning论文链接：https://arxiv.org/abs/1312.5602[https://arxiv.org/abs/1312.5602]引用：...
-
[Chapter 6] Reinforcement Learning (4) Policy Search
In the previous sections, we try to learn the utility function, or more ...
-
[Chapter 5] Reinforcement Learning (3) Function Approximation and Going Deep
Function Approximation While we are learning the Q-functions, but how to...
-
[Chapter 4] Reinforcement Learning (2) Model-Free Method
Model-Free RL Method In model-based method, we need firstly model the en...
-
[Chapter 3] Reinforcement Learning (1) Model-Based Method
Reinforcement Learning Firstly, we assume that all the environments in t...
-
[Chapter 2] Value Iteration and Policy Iteration
We now know the most important thing for computing an optimal policy is ...