stable-baselines3 VS cleanrl

Compare stable-baselines3 vs cleanrl and see what are their differences.

cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG) (by vwxyzjn)
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stable-baselines3 cleanrl
46 41
7,704 4,283
4.7% -
8.2 6.7
7 days ago 22 days ago
Python Python
MIT License 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.

stable-baselines3

Posts with mentions or reviews of stable-baselines3. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-09.

cleanrl

Posts with mentions or reviews of cleanrl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-24.

What are some alternatives?

When comparing stable-baselines3 and cleanrl you can also consider the following projects:

Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

tianshou - An elegant PyTorch deep reinforcement learning library.

Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥

SuperSuit - A collection of wrappers for Gymnasium and PettingZoo environments (being merged into gymnasium.wrappers and pettingzoo.wrappers

Tic-Tac-Toe-Gym - This is the Tic-Tac-Toe game made with Python using the PyGame library and the Gym library to implement the AI with Reinforcement Learning

rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.