rlpyt（Deep Reinforcement Learning in PyTorch）
rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch
Github：https://github.com/astooke/rlpyt
Introduction (CH)：https://baijiahao.baidu.com/s?id=1646437256939374418&wfr=spider&for=pc
Introduction (EN)：https://bair.berkeley.edu/blog/2019/09/24/rlpyt/
Documentation：https://rlpyt.readthedocs.io/en/latest/
arxiv：https://arxiv.org/abs/1909.01500
对于DQN，实现了双重DQN、对偶DQN、分布DQN、优先经验回放（proportional prioritization）以及多步回报（缺乏带噪DQN的实现）。
Installation
-
Clone this repository to the local machine.
-
Install the anaconda environment appropriate for the machine.
conda env create -f linux_[cpu|cuda9|cuda10].yml source activate rlpyt
- Either A) Edit the PYTHONPATH to include the rlpyt directory, or B) Install as editable python package
#A export PYTHONPATH=path_to_rlpyt:$PYTHONPATH #B pip install -e .
- Install any packages / files pertaining to desired environments (e.g. gym, mujoco). Atari is included.
pip install gym
Hint: for easy access, add the following to your ~/.bashrc (might substitute conda for source).
alias rlpyt="source activate rlpyt; cd path_to_rlpyt"
rlpyt/example/atari_dqn_async_cpu.py：设置n_socket=1；
rlpyt/example/atari_dqn_async_gpu.py：设置n_socket=1；
rlpyt/example/atari_dqn_async_serial.py：设置n_socket=1；