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.
This repository is a curated collection of research papers on Multi-Agent Reinforcement Learning (MARL), organized by categories such as framework, cooperation, communication, and applications. It serves as a reference for researchers and practitioners in the field. The repository contains no code, data, or executable components; it is purely a markdown file with links to papers. The list is actively maintained and includes recent papers up to 2025. It is not a software application or data pipeline, but a static paper list.