Extend Wave Function Collapse to Large-Scale Content Generation

Yuhe Nie, Shaoming Zheng, Zhan Zhuang, Xuan Song
8/14/2023
cs.AI

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Abstract

Wave Function Collapse (WFC) is a widely used tile-based algorithm in procedural content generation, including textures, objects, and scenes. However, the current WFC algorithm and related research lack the ability to generate commercialized large-scale or infinite content due to constraint conflict and time complexity costs. This paper proposes a Nested WFC (N-WFC) algorithm framework to reduce time complexity. To avoid conflict and backtracking problems, we offer a complete and sub-complete tileset preparation strategy, which requires only a small number of tiles to generate aperiodic and deterministic infinite content. We also introduce the weight-brush system that combines N-WFC and sub-complete tileset, proving its suitability for game design. Our contribution addresses WFC's challenge in massive content generation and provides a theoretical basis for implementing concrete games.

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Cite this paper

@article{nie2023extend,
  title  = {Extend Wave Function Collapse to Large-Scale Content Generation},
  author = {Yuhe Nie and Shaoming Zheng and Zhan Zhuang and Xuan Song},
  year   = {2023},
  eprint = {2308.07307},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.07307v1}
}

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