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    Automated iterative game design

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    ZOOK-DISSERTATION-2016.pdf (2.672Mb)
    Date
    2016-12-06
    Author
    Zook, Alexander
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    Abstract
    Computational systems to model aspects of iterative game design were proposed, encompassing: game generation, sampling behaviors in a game, analyzing game behaviors for patterns, and iteratively altering a game design. Explicit models of the actions in games as planning operators allowed an intelligent system to reason about how actions and action sequences affect gameplay and to create new mechanics. Metrics to analyze differences in player strategies were presented and were able to identify flaws in game designs. An intelligent system learned design knowledge about gameplay and was able to reduce the number of design iterations needed during playtesting a game to achieve a design goal. Implications for how intelligent systems augment and automate human game design practices are discussed.
    URI
    http://hdl.handle.net/1853/56346
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    • College of Computing Theses and Dissertations [1156]
    • Georgia Tech Theses and Dissertations [23403]
    • School of Interactive Computing Theses and Dissertations [130]

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