Automated Puzzle Difficulty Estimation

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    We introduce a method for automatically rating the difficulty of puzzle game levels. Our method takes multiple aspects of the levels of these games, such as level size, and combines these into a difficulty function. It can simply be adapted to most puzzle games, and we test it on three different ones: Flow, Lazors and Move. We conducted a user study to discover how difficult players find the levels of a set and use this data to train the difficulty function to match the user-provided ratings. Our experiments show that the difficulty function is capable of rating levels with an average error of approximately one point in Lazors and Move, and less than half a point in Flow, on a difficulty scale of 1-10.
    Original languageEnglish
    Title of host publication2015 IEEE Conference on Computational Intelligence and Games (CIG)
    PublisherIEEE
    Pages415-422
    Number of pages8
    ISBN (Print)978-1-4799-8621-7
    DOIs
    Publication statusPublished - 2015

    Keywords

    • Games
    • Color
    • Estimation
    • Rocks
    • Correlation
    • Time measurement
    • Linear programming
    • PSY
    • PUZ
    • AI

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