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Sturgeon-GRAPH: Constrained Graph Generation from Examples

Published:12 April 2023Publication History

ABSTRACT

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.

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  1. Sturgeon-GRAPH: Constrained Graph Generation from Examples

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    • Published in

      cover image ACM Other conferences
      FDG '23: Proceedings of the 18th International Conference on the Foundations of Digital Games
      April 2023
      621 pages
      ISBN:9781450398558
      DOI:10.1145/3582437

      Copyright © 2023 ACM

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      Publication History

      • Published: 12 April 2023

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