stable-baselines3 VS sample-factory

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

sample-factory

High throughput synchronous and asynchronous reinforcement learning (by alex-petrenko)
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stable-baselines3 sample-factory
46 6
7,704 721
4.7% -
8.2 8.1
7 days ago 23 days 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.
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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.

sample-factory

Posts with mentions or reviews of sample-factory. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-22.
  • A minimal RL library for infinite horizon tasks
    2 projects | /r/reinforcementlearning | 22 May 2023
    I take a lot of inspiration from Sample Factory and RLlib for my own RL library's implementation. Although I thoroughly enjoy both of these libraries, they just didn't quite fit right with my use case which motivated me to start my own. Hopefully someone finds use in rlstack whether it be through direct usage or as inspiration for their own personalized library
  • Fast and hackable frameworks for RL research
    4 projects | /r/reinforcementlearning | 8 Mar 2023
    I'm tired of having my 200m frames of Atari take 5 days to run with dopamine, so I'm looking for another framework to use. I haven't been able to find one that's fast and hackable, preferably distributed or with vectorized environments. Anybody have suggestions? seed-rl seems promising but is archived (and in TF2). sample-factory seems super fast but to the best of my knowledge doesn't work with replay buffers. I've been trying to get acme working but documentation is sparse and many of the features are broken.
  • How is IMPALA as a framework?
    2 projects | /r/reinforcementlearning | 1 Oct 2021
    Sample Factory: https://github.com/alex-petrenko/sample-factory
  • Best PyTorch RL library for doing research
    9 projects | /r/reinforcementlearning | 30 Apr 2021
    I borrow a lot of performance tricks from sample factory, which is awesome but hard to modify from its original APPO algorithm. rlpyt was more modular, and I borrowed more ideas from it (namedarraytuple), but still too limited.

What are some alternatives?

When comparing stable-baselines3 and sample-factory 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.