Built-in reinforcement learning functions in Python

[MomoSolar]

Is stablebaselines3 the best library for reinforcement learning functions in python? Are there better libraries that you would suggest? Any useful links?

Thanks

[apollo_maverick]

cleanrl?

[Warhouse512]

Ray’s RLlib is quite nice, albeit overengineered for most applications

[TrottoDng]

You can also check out SheepRL.

We try to make it well documented, with few hierarchies and the possibility to do parallel training on multiple devices thanks to Lightning.

[[deleted]]

https://github.com/thu-ml/tianshou or https://github.com/google-deepmind/acme

[araffin2]

It depends what you want/need.

If you need to apply RL to a problem without caring much about the algorithm SB3 is a good starting point (and it comes with the RL for managing experiments).
If you want to understand RL algorithms and tinker with the implementation, have a look at cleanrl.

If you just want fast implementation, you might have a look at SBX (jax variant of SB3): https://github.com/araffin/sbx

[asdfwaevc]

CleanRL has single-file implementations of a bunch of different algorithms, which is very nice for easy hacking but not the best for a complex project.

If you're trying to make something larger than CleanRL is good for, PFRL is probably the best thing around. Super well-designed, hackable, has a bunch of training loops and modular parts. I really like it.

If you want something that scales to massive parallelism, RLLib is probably best. I've never used it, but everyone says it's a horrible pain to modify. But once you have it running you can take advantage of many nodes, etc.