Generative Adversarial Imitation Learning with PyTorch

This repository is for a simple implementation of Generative Adversarial Imitation Learning (GAIL) with PyTorch. This implementation is based on the original GAIL paper (link), and my Reinforcement Learning Collection repository (link).

In this repository, MuJoCo environments such as Walker2d-v4, Hopper-v4, and Humanoid-v4 are used. You need to install them before running this repository.

Note: The environment's names could be different depending on the version of OpenAI Gym.

Install Dependencies

1. Install Python 3.

2. Install the Python packages in requirements.txt. If you are using a virtual environment for Python package management, you can install all python packages needed by using the following bash command:

   $ pip install -r requirements.txt
   $ pip install torch
   $ pip install gymnasium[mujoco]

Training and Running

1. Modify config.json as your machine setting.

2. Execute training process by train.py. An example of usage for train.py are following:

   $ python ensemble.py --env_name=Walker2d-v4 --num_bags=3 --num_layers=3

   The following bash command will help you:

   $ python train.py -h

References

• The original GAIL paper: link
• Reinforcement Learning Collection with PyTorch: link