SuperSuit is a Python library that provides a collection of lightweight, composable 'microwrappers' for preprocessing reinforcement learning environments. It supports both single-agent Gymnasium environments and multi-agent PettingZoo environments (AEC and Parallel APIs). The wrappers cover common transformations such as color reduction, frame stacking, resizing, dtype conversion, reward clipping, action scaling, and NaN handling. Additionally, it offers vectorization utilities to run multiple environment instances in parallel, including synchronous, asynchronous, and multiprocessing-based vector environments. The library is designed to be used as a preprocessing pipeline before feeding environments into RL algorithms. It is maintained primarily for compatibility with newer versions of PettingZoo and Gymnasium, with the stated intention of eventually merging relevant functionality into PettingZoo's own wrappers.
Craftium is a voxel-based game engine (Luanti/Minetest fork) extended with reinforcement learning capabilities. The core system provides a moddable 3D world with block-based gameplay, Lua scripting API, client-server architecture, and procedural map generation. The craftium add-on supplies Python bindings, Gymnasium environment interfaces, and RL training scripts to enable machine learning research within the game world. The system supports both traditional gameplay and AI experimentation through environment-specific mods that define reward functions, observations, and termination conditions for agents.