MineLand provides a flexible 3D sandbox environment inspired by Minecraft for training reinforcement learning agents. It features Gym-compatible APIs for seamless integration with existing RL libraries such as Stable Baselines, RLlib, and custom implementations. Users gain access to a library of tasks, including resource collection, navigation, and construction challenges, each with configurable difficulty and reward structures. Real-time rendering, multi-agent scenarios, and headless modes allow for scalable training and benchmarking. Developers can design new maps, define custom reward functions, and plugin additional sensors or controls. MineLand’s open-source codebase fosters reproducible research, collaborative development, and rapid prototyping of AI agents in complex virtual worlds.

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