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Sample-factory Alternatives
Similar projects and alternatives to sample-factory
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stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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InfluxDB
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machin
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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seed_rl
Discontinued SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
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Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
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dopamine
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better sample-factory alternative or higher similarity.
sample-factory reviews and mentions
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.
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A minimal RL library for infinite horizon tasks
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
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Fast and hackable frameworks for RL research
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.
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Multi-agent Decentralized Training with a PettingZoo environment
Hi, try sample-factory
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How is IMPALA as a framework?
Sample Factory: https://github.com/alex-petrenko/sample-factory
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The Myth of a Superhuman AI
Everything in this reply is wrong.
In AlphaZero for example, there were 44 million training games total for 700,00x0 steps of training for the full 9 hours.
Turning that human-like numbers, 44million games with on average 60 moves, at 1 second thinking time per move,
> 44000000*60/60/60/24/365 = 83,7138508371 years of training experience in 9 hours
The whole field of Reinforcement learning has agents training and playing games for many orders of magnitude more time than a human ever will. In-fact, we can scale this to over 100k of actions per second, in a single machine:
https://github.com/alex-petrenko/sample-factory
Then, there is also distributed Reinforcement Learning, where hundreds of agents can play at different machines and share experience, see AlphaZero, LeelaZero, R2D2 agent, R2D3 agent, Apex, Acer, Asynchronous PPO.
> but the data isn't useful without the context of experience
The experience is the data in Reinforcement Learning.
> and all processing power can do it overfit model without experience.
That is wrong, the agents perform what is called exploration to avoid getting stuck in simple strategies.
> Even if we put AI into an army of robots running around and experiencing things, there are still scaling limits to encoding and communicating knowledge and understanding.
True, but machines scale better because they speak the same language, or they can learn to tune their language to get their message across.
> Human organizations are a great example of the scaling limits of intelligence.
Human organization is a testament to how far we can get with something as limiting as the commonly used language. The language that we use to communicate is subject to misinterpretation due to our subjective experiences, this limitation is not shared by machines.
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Best PyTorch RL library for doing research
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.
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Stats
Basic sample-factory repo stats
6
738
8.1
about 2 months ago
alex-petrenko/sample-factory is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of sample-factory is Python.
Popular Comparisons
- sample-factory VS cleanrl
- sample-factory VS stable-baselines3
- sample-factory VS tianshou
- sample-factory VS machin
- sample-factory VS rl8
- sample-factory VS rlpyt
- sample-factory VS torchbeast
- sample-factory VS Deep-Reinforcement-Learning-Algorithms-with-PyTorch
- sample-factory VS mtrl
- sample-factory VS dopamine
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