dm_control VS mujoco-py

Compare dm_control vs mujoco-py and see what are their differences.

dm_control

Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. (by google-deepmind)

mujoco-py

MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3. (by openai)
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dm_control mujoco-py
7 3
3,520 2,731
2.0% 1.4%
7.5 0.0
5 days ago 4 months ago
Python Cython
Apache License 2.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

dm_control

Posts with mentions or reviews of dm_control. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-25.

mujoco-py

Posts with mentions or reviews of mujoco-py. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-18.

What are some alternatives?

When comparing dm_control and mujoco-py you can also consider the following projects:

gym - A toolkit for developing and comparing reinforcement learning algorithms.

baselines - OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

IsaacGymEnvs - Isaac Gym Reinforcement Learning Environments

pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

Robotics Library (RL) - The Robotics Library (RL) is a self-contained C++ library for rigid body kinematics and dynamics, motion planning, and control.

acme - A library of reinforcement learning components and agents

dreamerv2 - Mastering Atari with Discrete World Models

crafter - Benchmarking the Spectrum of Agent Capabilities

lab - A customisable 3D platform for agent-based AI research

myosuite - MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.

PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities