Sturgeon-GRAPH: Constrained Graph Generation from Examples
Seth Cooper · 2023
Procedural level generation techniques that learn local neighborhoods from example levels (such as WaveFunctionCollapse) have risen in popularity. Usually the neighborhood structure (such as a regular grid) onto which a level is generated is fixed in advance and not generated. In this work, we present a constraint-based approach for graph generation that learns local neighborhood patterns (in the form of labeled nodes and edges) from example graphs. This allows the approach to generate graphs with varying structures that are still locally similar to the examples. We demonstrate the approach on several applications, such as abstract graphs describing Legend of Zelda dungeons. Additionally, using Super Mario Bros. levels, we show how techniques that run on a grid may be considered a special case of graph generation where each tile is a node connecting to its neighboring tiles’ nodes.