Exploring game space of minimal action games via parameter tuning and survival analysis

Aaron Isaksen, Dan Gopstein, Julian Togelius, Andy Nealen

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Game designers can use computer-aided game design methods to model how players may experience the perceived difficulty of a game. We present methods to generate and analyze the difficulty of a wide variety of minimal action game variants throughout game space, where each point in this abstract design space represents a unique game variant. Focusing on a parameterized version of Flappy Bird, we predict hazard rates and difficulty curves using automatic playtesting, Monte Carlo simulation, a player model based on human motor skills (precision and actions per second), and survival analysis of score histograms. We demonstrate our techniques using simulated game play and actual game data from over 106 million play sessions of a popular online Flappy Bird variant, showing quantitative reasons why balancing a game for a wide range of player skill can be difficult. Some applications of our techniques include searching for a specific difficulty, game space visualization, computational creativity to find unique variants, and tuning game balance to adjust the difficulty curve even when game parameters are time varying, score dependent, or changing based on game progress. 2017 IEEE.

    Original languageEnglish (US)
    Article number8030128
    Pages (from-to)182-194
    Number of pages13
    JournalIEEE Transactions on Games
    Volume10
    Issue number2
    DOIs
    StatePublished - Jun 2018

    Keywords

    • Automated playtesting
    • Computer-aided game design
    • Flappy Bird
    • Player modeling
    • Survival analysis

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Software
    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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