This repo contains code for our paper Learning Belief Representations for Imitation Learning in POMDPs published at UAI 2019.
The code was tested with the following packages:
- python 3.6.6
- pytorch 0.4.1
- gym 0.10.8
To run MuJoCo experiments, use the script run_mujoco.sh with the following usage:
bash run_mujoco.sh [env] [belief_loss_type] [belief_regularization]
BMIL results can be reproduced with bash run_mujoco.sh [env] task_aware True
Please update the path to expert trajectories in the file "code/conf/envParams.yaml". Also see the storage requirements in "code/expert_envs.py" and modify as per convenience.
The base for this code is provided by DVRL, which itself utilizes methods from this. We also use OpenAI baselines helpers for vectorized environments.