LEXA Benchmark

Codebase for the self-supervised goal reaching benchmark introduced in the LEXA paper (Discovering and Achieving Goals via World Models, NeurIPS 2021).


Create the conda environment by running : conda env create -f environment.yml

Alternatively, you can update an existing conda environment by running : conda env update -f environment.yml

Modify the python path
export PYTHONPATH=<path to lexa-benchmark>

Export the following variables for rendering
export MUJOCO_RENDERER=egl; export MUJOCO_GL=egl

Please follow these instructions to install mujoco


If you find this code useful, please cite:

    title={Discovering and Achieving Goals via World Models},
    author={Mendonca, Russell and Rybkin, Oleh and
    Daniilidis, Kostas and Hafner, Danijar and Pathak, Deepak},


This benchmark is built on top of the following environments: Adept, MetaWorld, and DeepMind Control Suite.


View Github