This repository contains the code to reproduce the experimental results of ATAC algorithm in the paper Adversarially Trained Actor Critic for Offline Reinforcement Learning by Ching-An Cheng, Tengyang Xie, Nan Jiang, and Alekh Agarwal (https://arxiv.org/abs/2202.02446).
***Please see also https://github.com/microsoft/lightATAC for a lightweight reimplementation of ATAC, which gives a 1.5-2X speed up compared with the original code here.
git clone https://github.com/microsoft/ATAC.git
conda create -n atac python=3.8
cd atac
(Optional) Install free mujoco210 for mujoco_py and mujoco211 for dm_control.
bash install_mujoco.sh
echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mujoco210/bin:/usr/lib/nvidia" >> ~/.bashrc
source ~/.bashrc
conda activate atac
pip install -e .[mujoco210]
# or below, if the original paid mujoco is used.
pip install -e .[mujoco200]
python scripts/main.py
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