Evaluation of a recommender system for assisting novice game designers

Tiago Machado, Daniel Gopstein, Angela Wang, Oded Nov, Andrew Nealen, Julian Togelius

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

    Abstract

    Game development is a complex task involving multiple disciplines and technologies. Developers and researchers alike have suggested that AI-driven game design assistants may improve developer workflow. We present a recommender system for assisting humans in game design as well as a rigorous human subjects study to validate it. The AI-driven game design assistance system suggests game mechanics to designers based on characteristics of the game being developed. We believe this method can bring creative insights and increase user's productivity. We conducted quantitative studies that showed the recommender system increases users' levels of accuracy and computational affect, and decreases their levels of workload.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019
    PublisherAAAI press
    Pages167-173
    Number of pages7
    ISBN (Electronic)9781577358190
    StatePublished - 2019
    Event15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019 - Atlanta, United States
    Duration: Oct 8 2019Oct 12 2019

    Publication series

    NameProceedings of the 15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019

    Conference

    Conference15th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2019
    CountryUnited States
    CityAtlanta
    Period10/8/1910/12/19

    ASJC Scopus subject areas

    • Visual Arts and Performing Arts
    • Artificial Intelligence

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