dm_control

dm_control

dm_control is Google DeepMind's software stack for physics-based simulation and reinforcement learning research. It wraps the MuJoCo physics engine with a clean Python API and provides a comprehensive suite of continuous-control tasks (the DeepMind Control Suite) that have become a standard benchmark in RL research.

Key Features

• Python bindings for the full MuJoCo C API via dm_control.mujoco
• DeepMind Control Suite: 28 physics tasks across locomotion, manipulation, and more
• Composer framework for procedurally assembling complex tasks from reusable components
• Locomotion arena library with varied terrains and procedural mazes
• Pixel and state observations, off-screen rendering, and deterministic resets

Quick Start

pip install dm-control

from dm_control import suite
import numpy as np

env = suite.load("cheetah", "run")
action_spec = env.action_spec()
timestep = env.reset()
while not timestep.last():
    action = np.random.uniform(action_spec.minimum, action_spec.maximum)
    timestep = env.step(action)
    print(timestep.reward)

npx ai-supply add dm-control-physics-rl

Curated mirror of the open-source dm_control (Apache-2.0). Get it from the source.