Date of Completion
5-5-2023
Degree Type
Honors Thesis
Discipline
Computer Science (CMSI)
First Advisor
Tyler Edmiston
Abstract
In this file, I present a sequence of algorithms that handle procedural level generation for the game Fragment, a game designed for CMSI 4071 and CMSI 4071 in collaboration with students from the LMU Animation department. I use algorithms inspired by graph theory and implementing best practices to the best of my ability. The full level generation sequence is comprised of four algorithms: the terrain generation, boss room placement, player spawn point selection, and enemy population. The terrain generation algorithm takes advantage of tree traversal methods to create a connected graph of walkable tiles. The boss room placement algorithm randomly places the boss’s arena on the map. The player spawn point selection algorithm randomly chooses a tile on which the player will begin the level, avoiding tiles that are adjacent to cliffs. The enemy spawn placement algorithm has a chance to randomly place an enemy on each walkable tile not within 3 tiles of the player or inside the boss arena. These four simple algorithms, when combined, plus additional helper methods to make the map more aesthetically pleasing, allow Fragment to generate a theoretically limitless amount of content.
Recommended Citation
Ahn, Kieran and Edmiston, Tyler, "Procedural Level Generation For A Top-Down Roguelike Game" (2023). Honors Thesis. 454.
https://digitalcommons.lmu.edu/honors-thesis/454
Included in
Other Computer Sciences Commons, Software Engineering Commons, Theory and Algorithms Commons