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The evolution of fun: a generic model of video game challenge for automatic level design

Resource type
Thesis type
(Thesis) M.Sc.
Date created
This thesis presents an approach to automatic video game level design consisting of a novel computational model of player enjoyment and a generative system based on evolutionary computing. The model is grounded in player experience research and game design theory and is used to estimate the entertainment value of game levels as a function of their constituent rhythm groups: alternating periods of high and low challenge. In comparison to existing, bottom-up techniques such as rule-based systems, the model affords a number of distinct advantages: it can be generalized to different types of games; it provides adjustable parameters representing semantically meaningful concepts such as difficulty and player skill; and it can facilitate mixed-initiative collaboration between the automated system and a human designer. The generative system represents a unique combination of genetic algorithms and constraint solving methods and leverages the model to create fun levels for two different games.
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Copyright is held by the author.
The author granted permission for the file to be printed and for the text to be copied and pasted.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: DiPaola, Steve
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etd6326_NSorenson.pdf 5.39 MB

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