meltingpot VS dm_control

Compare meltingpot vs dm_control and see what are their differences.

meltingpot

A suite of test scenarios for multi-agent reinforcement learning. (by google-deepmind)

dm_control

Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. (by google-deepmind)
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meltingpot dm_control
4 7
541 3,569
4.3% 1.9%
8.7 7.5
13 days ago 6 days ago
Python Python
Apache License 2.0 Apache License 2.0
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.

meltingpot

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

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.

What are some alternatives?

When comparing meltingpot and dm_control you can also consider the following projects:

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

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

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

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

Shimmy - An API conversion tool for popular external reinforcement learning environments

IsaacGymEnvs - Isaac Gym Reinforcement Learning Environments

open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

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).

stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

mujoco-py - MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.

Arcade-Learning-Environment - The Arcade Learning Environment (ALE) -- a platform for AI research.

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