RLMeta – a light-weight flexible framework for Distributed Reinforcement Learning Research

rlmeta – a flexible lightweight research framework for Distributed
Reinforcement Learning based on PyTorch and
moolib

Installation

To build from source, please install PyTorch first,
and then run the commands below.

$ git clone https://github.com/facebookresearch/rlmeta
$ cd rlmeta
$ git submodule sync && git submodule update --init --recursive
$ pip install -e .

Run an Example

To run the example for Atari Pong game with PPO algorithm:

$ cd examples/atari/ppo
$ python atari_ppo.py env="PongNoFrameskip-v4" num_epochs=20

We are using hydra to define

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