# Modular Procedural Generation for Voxel Maps

arXiv: https://arxiv.org/abs/2104.08890 · HTML: https://mlsanity.com/paper/2104.08890/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 29 references that are in the map.
- First posted on arXiv 18 Apr 2021.

## Builds on (most cited first, 6 of 6)

- [MineRL: A Large-Scale Dataset of Minecraft Demonstrations](https://mlsanity.com/paper/1907.13440/) (2019)
- [The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors](https://mlsanity.com/paper/2101.11071/) (2021)
- [CraftAssist: A Framework for Dialogue-enabled Interactive Agents](https://mlsanity.com/paper/1907.08584/) (2019)
- [Generative Design in Minecraft (GDMC), Settlement Generation Competition](https://mlsanity.com/paper/1803.09853/) (2018)
- [Why Build an Assistant in Minecraft?](https://mlsanity.com/paper/1907.09273/) (2019)
- [Organic Building Generation in Minecraft](https://mlsanity.com/paper/1906.05094/) (2019)

## Built on by (most cited first, 1 of 1)

- [Voxify3D: Pixel Art Meets Volumetric Rendering](https://mlsanity.com/paper/2512.07834/) (2025)

## Abstract (arXiv)

Task environments developed in Minecraft are becoming increasingly popular for artificial intelligence (AI) research. However, most of these are currently constructed manually, thus failing to take advantage of procedural content generation (PCG), a capability unique to virtual task environments. In this paper, we present mcg, an open-source library to facilitate implementing PCG algorithms for voxel-based environments such as Minecraft. The library is designed with human-machine teaming research in mind, and thus takes a 'top-down' approach to generation, simultaneously generating low and high level machine-readable representations that are suitable for empirical research. These can be consumed by downstream AI applications that consider human spatial cognition. The benefits of this approach include rapid, scalable, and efficient development of virtual environments, the ability to control the statistics of the environment at a semantic level, and the ability to generate novel environments in response to player actions in real time.