Mech-Elites: Illuminating the Mechanic Space of GVG-AI

Megan Charity, Michael Cerny Green, Ahmed Khalifa, Julian Togelius

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

    Abstract

    This paper introduces a fully automatic method of mechanic illumination for general video game level generation. Using the Constrained MAP-Elites algorithm and the GVG-AI framework, this system generates the simplest tile based levels that contain specific sets of game mechanics and also satisfy playability constraints. We apply this method to illuminate the mechanic space for four different games in GVG-AI: Zelda, Solarfox, Plants, and RealPortals. With this system, we can generate playable levels that contain different combinations of most of the possible mechanics. These levels can later be used to populate game tutorials that teach players how to use the mechanics of the game.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 15th International Conference on the Foundations of Digital Games, FDG 2020
    EditorsGeorgios N. Yannakakis, Antonios Liapis, Kyburz Penny, Vanessa Volz, Foaad Khosmood, Phil Lopes
    PublisherAssociation for Computing Machinery
    ISBN (Electronic)9781450388078
    DOIs
    StatePublished - Sep 15 2020
    Event15th International Conference on the Foundations of Digital Games, FDG 2020 - Bugibba, Malta
    Duration: Sep 15 2020Sep 18 2020

    Publication series

    NameACM International Conference Proceeding Series

    Conference

    Conference15th International Conference on the Foundations of Digital Games, FDG 2020
    Country/TerritoryMalta
    CityBugibba
    Period9/15/209/18/20

    Keywords

    • evolutionary algorthims
    • general video game
    • level generation
    • map elites
    • procedural content generation

    ASJC Scopus subject areas

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

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