Automated iterative game design

Artificial intelligence;Machine learning;Game design;Computational creativity;Games

Zook, Alexander ; Riedl, Mark O. Magerko, Brian Interactive Computing Isbell, Charles Goel, Ashok Mateas, Michael Orkin, Jeff ; Riedl, Mark O.

University:Georgia Institute of Technology

Department:Interactive Computing

关键词: Artificial intelligence;    Machine learning;    Game design;    Computational creativity;    Games;   

Others  :  https://smartech.gatech.edu/bitstream/1853/56346/1/ZOOK-DISSERTATION-2016.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

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.