Lode Enhancer: Level Co-creation Through Scaling

Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis, Ahmed Khalifa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We explore AI-powered upscaling as a design assistance tool in the context of creating 2D game levels. Deep neural networks are used to upscale artificially downscaled patches of levels from the puzzle platformer game Lode Runner. The trained networks are incorporated into a web-based editor, where the user can create and edit levels at three different levels of resolution: 4x4, 8x8, and 16x16. An edit at any resolution instantly transfers to the other resolutions. As upscaling requires inventing features that might not be present at lower resolutions, we train neural networks to reproduce these features. We introduce a neural network architecture that is capable of not only learning upscaling but also giving higher priority to less frequent tiles. To investigate the potential of this tool and guide further development, we conduct a qualitative study with 3 designers to understand how they use it. Designers enjoyed co-designing with the tool, liked its underlying concept, and provided feedback for further improvement.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 18th International Conference on the Foundations of Digital Games, FDG 2023
    EditorsPhil Lopes, Filipe Luz, Antonios Liapis, Henrik Engstrom
    PublisherAssociation for Computing Machinery
    ISBN (Electronic)9781450398565
    DOIs
    StatePublished - Apr 12 2023
    Event18th International Conference on the Foundations of Digital Games, FDG 2023 - Lisbon, Portugal
    Duration: Apr 11 2023Apr 14 2023

    Publication series

    NameACM International Conference Proceeding Series

    Conference

    Conference18th International Conference on the Foundations of Digital Games, FDG 2023
    Country/TerritoryPortugal
    CityLisbon
    Period4/11/234/14/23

    Keywords

    • mixed-initiative
    • neural networks
    • procedural content generation
    • supervised learning
    • upscaling

    ASJC Scopus subject areas

    • Human-Computer Interaction
    • Computer Networks and Communications
    • Computer Vision and Pattern Recognition
    • Software

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