stable-baselines3 VS mtrl

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

mtrl

Multi Task RL Baselines (by facebookresearch)
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stable-baselines3 mtrl
46 1
7,704 211
4.7% -
8.2 0.0
6 days ago about 2 years ago
Python Python
MIT License MIT License
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.

mtrl

Posts with mentions or reviews of mtrl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-30.

What are some alternatives?

When comparing stable-baselines3 and mtrl 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

cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

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. đŸ”„

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.