/CausalCuriosity

Official implementation of Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning at ICML 2021.

Primary LanguagePython

Causal Curiosity

Official implementation of Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning at ICML 2021. Paper and Website

Installation

Download our version of CausalWorld from this drive link. Once downloaded add it to this repository and follow instructions to install CausalWorld.

You will also need mujoco-py. Follow the installation instructions here. After installing mujoco-py, you will need to edit the done property for each of the mujoco agents property files. The done property needs to be set to False. Otherwise the environment will stop simulating if the agents orientation exceeds a threshold.

Usage

For Mujoco experiments, run

python pnw_mujoco.py

For CausalWorld experiments, run

python plan_and_write_video_vanilla_cw.py

Citation

@article{sontakke2020causal,
  title={Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning},
  author={Sontakke, Sumedh A and Mehrjou, Arash and Itti, Laurent and Sch{\"o}lkopf, Bernhard},
  journal={arXiv preprint arXiv:2010.03110},
  year={2020}
}