Visual Adversarial Imitation Learning using Variational Models (VMAIL)

This is the official implementation of the NeurIPS 2021 paper.

Method

VMAIL simultaneously learns a variational dynamics model and trains an on-policy
adversarial imitation learning algorithm in the latent space using only model-based
rollouts. This allows for stable and sample efficient training, as well as zero-shot
imitation learning by transfering the learned dynamics model

Instructions

Get dependencies:

conda env create -f vmail.yml
conda activate vmail
cd robel_claw/robel
pip install -e .

To train agents for each environmnet download the expert data from the provided link and run: