@inproceedings{e4dd732bba4b48f2ac1b56041a3a6ef3,
title = "Terrain-adaptive PCGML in Minecraft",
abstract = "We make a first step towards terrain-adaptive PCGML in Minecraft by introducing an automated system to create “volume-to-volume” datasets suitable for machine learning by leveraging handwritten black-box Minecraft settlement generation algorithms. Using this system, we create ten terrain-adaptive Minecraft ML datasets - including ones based on the currently best-performing algorithm submitted to the Generative Design in Minecraft (GDMC) competition. Finally, we train and qualitatively evaluate various GAN-based volume-to-volume models on all ten of our datasets. Although we do not obtain good results in all cases, we demonstrate that terrain-adaptive PCGML in Minecraft is indeed feasible.",
keywords = "GAN, Minecraft, PCG, PCGML",
author = "Staaij, {A. van der} and M. Preuss and C. Salge",
note = "{\textcopyright} 2024 IEEE.",
year = "2024",
month = aug,
day = "28",
doi = "10.1109/CoG60054.2024.10645652",
language = "English",
series = "IEEE Conference on Computatonal Intelligence and Games, CIG",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "1--8",
booktitle = "Proceedings of the 2024 IEEE Conference on Games, CoG 2024",
address = "United States",
}