Modular Procedural Generation for Voxel Maps
Adarsh Pyarelal, Aditya Banerjee, Kobus Barnard

TL;DR
This paper introduces mcg, an open-source library for procedural generation of voxel maps like Minecraft, enabling scalable, real-time environment creation tailored for AI research and human-machine teaming.
Contribution
The paper presents mcg, a novel library that facilitates top-down procedural content generation for voxel environments, integrating semantic control and real-time responsiveness.
Findings
Enables rapid and scalable environment generation.
Supports semantic-level control of environment statistics.
Allows real-time adaptation to player actions.
Abstract
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…
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Taxonomy
TopicsGeographic Information Systems Studies · Data Management and Algorithms · Advanced Image and Video Retrieval Techniques
