Sturgeon-MKIV: Constraint-Based Level and Playthrough Generation with Graph Label Rewrite Rules

Procedurally generated game levels should be completable. The representation used for levels and game mechanics impacts the types of games for which different techniques can be applied. Previous work used a constraint solving approach to simultaneously generate levels with example playthroughs, showing they can be completed using the game's mechanics. However, that work used 2D grid-based rewrite rules. In this work, we extend previous approaches by representing levels as more general graphs, and game mechanics as rewrites on node and edge labels of subgraphs. Using this approach, graph-based levels with playthroughs are generated. We describe the approach and demonstrate its application in some games with graph-based levels.

Authors

Institutions

Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Published
2024-11-15
DOI
https://doi.org/10.1609/aiide.v20i1.31862
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sturgeon-MKIV: Constraint-Based Level and Playthrough Generation with Graph Label Rewrite Rules

Seth Cooper, Mahsa Bazzaz
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Data Mining Algorithms and Applications
article

Sturgeon-MKIV: Constraint-Based Level and Playthrough Generation with Graph Label Rewrite Rules

Seth Cooper, Mahsa Bazzaz
article en

Abstract

Procedurally generated game levels should be completable. The representation used for levels and game mechanics impacts the types of games for which different techniques can be applied. Previous work used a constraint solving approach to simultaneously generate levels with example playthroughs, showing they can be completed using the game's mechanics. However, that work used 2D grid-based rewrite rules. In this work, we extend previous approaches by representing levels as more general graphs, and game mechanics as rewrites on node and edge labels of subgraphs. Using this approach, graph-based levels with playthroughs are generated. We describe the approach and demonstrate its application in some games with graph-based levels.

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital EntertainmentVol. 20(1)
Universidad del Noreste (MX)
Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Data Mining Algorithms and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.