You have an environment, a model, and a reinforcement learning library that are designed to work together but don't. PufferLib makes them play nice. The library provides one-line environment wrappers that eliminate common compatibility problems and fast vectorization to accelerate training. With PufferLib, you can use familiar libraries like CleanRL and SB3 to scale from classic benchmarks like Atari and Procgen to complex simulators like NetHack and Neural MMO. We release pip packages and prebuilt images with dependencies for dozens of environments. All of our code is free and open-source software under the MIT license, complete with baselines, documentation, and support at pufferai.github.io.

Reinforcement learning has become a trending topic among all the tech giants and none of them is sitting back to catch up on this. OpenAI Baselines is a set of high-quality implementations of reinforcement learning algorithms. These algorithms make it easier for the research community to replicate, refine, and identify new ideas to create good baselines to build research on top of. They have beautifully abstracted the details of the RL algorithms and have made the use of these techniques as easy as calling a single class and feeding it essential details like environment name and batch sizes. This has made experimentation much easier and implementation simpler for the people new to the field.