Predicting Personas Using Mechanic Frequencies and Game State Traces

Michael Cerny Green, Ahmed Khalifa, M. Charity, Debosmita Bhaumik, Julian Togelius

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

    Abstract

    We investigate how to efficiently predict play personas based on playtraces. Play personas can be computed by calculating the action agreement ratio between a player and a generative model of playing behavior, a so-called procedural persona. But this is computationally expensive and assumes that appropriate procedural personas are readily available. We present two methods for estimating play personas, one using regular supervised learning and aggregate measures of game mechanics initiated, and another based on sequence learning on a trace of closely cropped gameplay observations. While both of these methods achieve high accuracy when predicting play personas defined by agreement with procedural personas, they utterly fail to predict play style as defined by the players themselves using a questionnaire. This interesting result highlights the value of using computational methods in defining play personas.

    Original languageEnglish (US)
    Title of host publication2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781665467087
    DOIs
    StatePublished - 2022
    Event2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Padua, Italy
    Duration: Jul 18 2022Jul 23 2022

    Publication series

    Name2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings

    Conference

    Conference2022 IEEE Congress on Evolutionary Computation, CEC 2022
    Country/TerritoryItaly
    CityPadua
    Period7/18/227/23/22

    Keywords

    • game mechanics
    • machine learning
    • play persona
    • player modeling
    • videogames

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Computational Mathematics
    • Control and Optimization

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