Mario Level Generation from Mechanics Using Scene Stitching

Michael Cerny Green, Luvneesh Mugrai, Ahmed Khalifa, Julian Togelius

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


    Video game tutorials allow players to gain mastery over game skills and mechanics. To hone players' skills, it is beneficial from practicing in environments that promote individual player skill sets. However, automatically generating environments which are mechanically similar to one-another is a non-trivial problem. This paper presents a level generation method for Super Mario by stitching together pre-generated "scenes"that contain specific mechanics, using mechanic-sequences from agent playthroughs as input specifications. Given a sequence of mechanics, the proposed system uses an FI-2Pop algorithm and a corpus of scenes to perform automated level authoring. The proposed system outputs levels that can be beaten using a similar mechanical sequence to the target mechanic sequence but with a different playthrough experience. We compare the proposed system to a greedy method that selects scenes that maximize the number of matched mechanics. Unlike the greedy approach, the proposed system is able to maximize the number of matched mechanics while reducing emergent mechanics using the stitching process.

    Original languageEnglish (US)
    Title of host publicationIEEE Conference on Games, CoG 2020
    PublisherIEEE Computer Society
    Number of pages8
    ISBN (Electronic)9781728145334
    StatePublished - Aug 2020
    Event2020 IEEE Conference on Games, CoG 2020 - Virtual, Osaka, Japan
    Duration: Aug 24 2020Aug 27 2020

    Publication series

    NameIEEE Conference on Computatonal Intelligence and Games, CIG
    ISSN (Print)2325-4270
    ISSN (Electronic)2325-4289


    Conference2020 IEEE Conference on Games, CoG 2020
    CityVirtual, Osaka


    • Design Patterns
    • Evolutionary Algorithms
    • Experience Driven PCG
    • Feasible-Infeasible 2-Population
    • PCG
    • Stitching
    • Super Mario Bros

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Graphics and Computer-Aided Design
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction
    • Software


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