Lode Encoder: AI-constrained co-creativity

Debosmita Bhaumik, Ahmed Khalifa, Julian Togelius

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


    We present Lode Encoder, a gamified mixed-initiative level creation system for the classic platform-puzzle game Lode Runner. The system is built around several autoen-coders which are trained on sets of Lode Runner levels. When fed with the user's design, each autoencoder produces a version of that design which is closer in style to the levels that it was trained on. The Lode Encoder interface allows the user to build and edit levels through 'painting' from the suggestions provided by the autoencoders. Crucially, in order to encourage designers to explore new possibilities, the system does not include more traditional editing tools. We report on the system design and training procedure, as well as on the evolution of the system itself and user tests.

    Original languageEnglish (US)
    Title of host publication2021 IEEE Conference on Games, CoG 2021
    PublisherIEEE Computer Society
    ISBN (Electronic)9781665438865
    StatePublished - 2021
    Event2021 IEEE Conference on Games, CoG 2021 - Copenhagen, Denmark
    Duration: Aug 17 2021Aug 20 2021

    Publication series

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


    Conference2021 IEEE Conference on Games, CoG 2021


    • Co-Creation
    • Level Design
    • Machine Learning
    • Mixed Initiative
    • Variational Autoencoders

    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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