RLMeta – a light-weight flexible framework for Distributed Reinforcement Learning Research
rlmeta – a flexible lightweight research framework for DistributedReinforcement Learning based on PyTorch andmoolib 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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