learn_in_dmc.md

Install Gymnasium MuJoCo/DMC environments

First, you should install the proper environments:

• MuJoCo (Gymnasium): you need to install extra packages: use the pip install -e .[mujoco] command to have available all the MuJoCo environments provided by Gymnasium (https://gymnasium.farama.org/environments/mujoco/).
• DMC: you have to install extra packages with the following command: pip install -e .[dmc]. (https://github.com/deepmind/dm_control).

Install OpenGL rendering backands packages

MuJoCo/DMC supports three different OpenGL rendering backends: EGL (headless), GLFW (windowed), and OSMesa (headless). For each of them, you need to install some packages:

• GLFW: sudo apt-get install libglfw3 libglew2.2
• EGL: sudo apt-get install libglew2.2
• OSMesa: sudo apt-get install libgl1-mesa-glx libosmesa6 In order to use one of these rendering backends, you need to set the MUJOCO_GL environment variable to "glfw", "egl", "osmesa", respectively.

Note

The libglew2.2 could have a different name, based on your OS (e.g., libglew2.2 is for Ubuntu 22.04.2 LTS).

For more information: https://github.com/deepmind/dm_control and https://mujoco.readthedocs.io/en/stable/programming/index.html#using-opengl.

MuJoCo Gymnasium

In order to train your agents on the MuJoCo environments provided by Gymnasium, it is sufficient to select the MuJoCo environment (env=mujoco) and set the env.id to the name of the environment you want to use. For instance, "Walker2d-v4" if you want to train your agent in the walker walk environment.

python sheeprl.py exp=dreamer_v3 env=mujoco env.id=Walker2d-v4 algo.cnn_keys.encoder=[rgb]

DeepMind Control

In order to train your agents on the DeepMind control suite, you have to select the DMC environment (env=dmc) and set the id of the environment you want to use. A list of the available environments can be found here. For instance, if you want to train your agent on the walker walk environment, you need to set the env.id to "walker_walk".

python sheeprl.py exp=dreamer_v3 env=dmc env.id=walker_walk algo.cnn_keys.encoder=[rgb]

Note

By default the env.sync_env parameter is set to True. We recommend not changing this value for the MuJoCo environments to work properly.