Abstract
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.
Advisor
Guarnera, Drew
Department
Computer Science
Recommended Citation
Suzue, Karen, "Adaptive NPC Behavior In Maze Chase Game Using Genetic Algorithms" (2022). Senior Independent Study Theses. Paper 9972.
https://openworks.wooster.edu/independentstudy/9972
Publication Date
2022
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis Exemplar
© Copyright 2022 Karen Suzue