The codebase contains elements from the BabyAI platform, the meta-mb codebase, the d4rl codebase, and denisyarats/pytorch_sac codebase.

The main branch of this repository is updated frequently. If you are looking to replicate or compare against the results from the NeurIPS paper, please use the code on the neurips_21 branch.

First, clone the repo.

Run the following commands:

git clone https://github.com/AliengirlLiv/teachable.git
conda create --name teachable_rl python=3.7
cd teachable
conda activate teachable_rl
sudo apt install libglew-dev libsm6 libxrender1 libosmesa6-dev patchelf
pip install -r reqs.txt

Add the project directory MY/PATH/TO/PROJECT/teachable to your PYTHONPATH.

If you want to use the Point Maze or Ant MAze environments, install Mujoco.

Add these to your ~/.bashrc file (note version numbers may have changed):

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/.mujoco/mujoco210/bin

Then run:

cd envs/d4rl
pip install -v --editable .

The most common installation error is mujoco not installing correctly. To check if this is the problem, open a python interpreter and run import mujoco_py.

To train a model, run the train_model.py script from the teachable directory.

Example: python scripts/train_model.py --prefix EXP_NAME --collect_with_rl_policy --level 2 --frames_per_proc 200 --num_envs 20 --rl_teacher OffsetWaypoint --env point_mass