Persona-driven Dominant/Submissive Map (PDSM) Generation for Tutorials

Michael Cerny Green, Ahmed Khalifa, Charity, Julian Togelius

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


    In this paper, we present a method for automated persona-driven video game tutorial level generation. Tutorial levels are scenarios in which the player can explore and discover different rules and game mechanics. Procedural personas can guide generators to create content which encourages or discourages certain playstyle behaviors. In this system, we use procedural personas to calculate the behavioral characteristics of levels which are evolved using the quality-diversity algorithm known as Constrained MAP-Elites. An evolved map's quality is determined by its simplicity: the simpler it is, the better it is. Within this work, we show that the generated maps can strongly encourage or discourage different persona-like behaviors and range from simple solutions to complex puzzle-levels, making them perfect candidates for a tutorial generative system.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 17th International Conference on the Foundations of Digital Games, FDG 2022
    EditorsKostas Karpouzis, Stefano Gualeni, Allan Fowler
    PublisherAssociation for Computing Machinery
    ISBN (Electronic)9781450397957
    StatePublished - Sep 5 2022
    Event17th International Conference on the Foundations of Digital Games, FDG 2022 - Athens, Greece
    Duration: Sep 5 2022Sep 8 2022

    Publication series

    NameACM International Conference Proceeding Series


    Conference17th International Conference on the Foundations of Digital Games, FDG 2022


    • evolution
    • experience driven level generation
    • procedural level generation
    • procedural persona
    • quality diversity

    ASJC Scopus subject areas

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


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