  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.
