The official code of "Adversarial Counterfactual Environment Model Learning".
We provide a faithful offline dynamics model learning technique based on the adversarial model learning paradigm.
The optimization pipeline of the proposed algorithm is as follows:
Also, you can see this Twitter thread for a brief discussion of this algorithm: https://x.com/xiong_hui_chen/status/1737597369514860803?s=20
install
pip install -e .
pip install -r requirements.txt
install RLAssistant for experiment management
git clone https://github.com/polixir/RLAssistant.git
cd RLAssistant
pip install -e .
run
cd run_scripts
python main.py --data_type d4rl --env_name hopper --data_train_type medium
view your results
- the tensorboard logs are in ./RLA_LOG/log folder;
- you can manager your experiment result via RLAssistant (see: https://github.com/polixir/RLAssistant)