Quick Start

After you install MyoAssist (see Getting Started), run one of these minimal scripts to confirm your setup builds and steps a composed environment. Neither one trains a policy. They only create an environment and run it, so you see something move in a minute.

Minimal RL environment

This creates a Gym-wrapped MuJoCo environment and steps it with random actions for about 150 frames (5 seconds).

python rl_train/run_sim_minimal.py

On macOS, use mjpython so the MuJoCo viewer works:

mjpython rl_train/run_sim_minimal.py

Minimal reflex controller (CO)

This builds a composed reflex environment, runs a random controller, and prints how long the model stays upright. The walking duration changes each run, because the control parameters are random.

cd ctrl_optim
python run_ctrl_minimal.py

Next steps

• Defining an Environment: choose the MSK model, device, and terrain to simulate.
• Examples: ready-to-run environment specs.
• Reinforcement Learning: train a policy.
• Controller Optimization: optimize a reflex controller.