Enhancing wave function collapse with design-level constraints

Abstract

Wave Function Collapse (WFC) is a non-backtracking, greedy search algorithm that is commonly known for its ability to take an example image and generate similar images. Since its inception, technical artists have explored the algorithm's extensibility and usability through various implementations spanning from 3D world generation to poetry creation. However, there has been no integration of design constraints into the generative process. In this paper, we explore WFC as a constraint satisfaction solver to integrate design principles and practices by modifying components within the algorithm. First, we extend the local constraint reasoning by incorporating non-local constraints as well as upper and lower bounds. Next, we further manipulate the generative space by introducing weight recalculation and dependencies. Lastly, we evaluate our design-focused variant of WFC against the original implementation to examine the associated costs in computational time and memory usage. In summary, this paper describes a technical implementation of integrating design constraints into WFC and analyzes the computational trade-offs.