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

1. Clone this repository to the local machine.

2. Install the anaconda environment appropriate for the machine.

conda env create -f linux_[cpu|cuda9|cuda10].yml
source activate rlpyt

3. 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 .

4. 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；