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Imitation Learning Baseline Implementations

This projects aim to provide clean implementations of imitation learning algorithms. Currently we have implementations of AIRL and GAIL, and intend to add more in the future.

To install:

sudo apt install libopenmpi-dev
conda create -n imitation python
conda activate imitation
pip install -r requirements.txt -r requirements-dev.txt
pip install -e .  # install yairl in developer mode

To run:

# train demos with normal AIRL
python scripts/data_collect.py --gin_config configs/cartpole_data_collect.gin
# do AIRL magic to get back reward from demos
python scripts/run_training.py --gin_config configs/cartpole_orig_airl_repro.gin

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A clean implementation of imitation learning algorithms

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  • Python 97.6%
  • Jupyter Notebook 1.7%
  • Shell 0.7%
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