Difficulty adjustment, although an important aspect of game development, is a tedious and costly process that produces uncertain results due to the wide range of skill among players. Most of the current approaches to difficulty adjustment in video games include fixed incremental difficulty curves, data generalization, and extensive manual playtesting. In this study, we explore genetic algorithms as an alternative approach to difficulty balancing with a focus on adjusting NPC behavior. A maze-chase game is built for demonstration purposes. Additionally, a genetic algorithm based on previous theoretical techniques is developed for the game.


Guarnera, Drew


Computer Science

Publication Date


Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis Exemplar


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