Graduation Year
2025
Document Type
Campus Only Senior Thesis
Degree Name
Bachelor of Arts
Department
Computer Science
Reader 1
Mark Huber
Reader 2
Jingyi Li
Reader 3
Matthew Pagoaga
Terms of Use & License Information
Abstract
This work is an art project that explores how different swarm algorithms, algorithms based on collective intelligent systems in nature, can make art from inputted audio. I use Processing, a software sketchbook, and a language often used for computational art, to visualize three different algorithms: KANTS, Particle Swarm Optimization (PSO), and BOIDS. I extend these algorithms’ behavior from ants, bees, and birds flocking to react visually to audio and compare the outputs based on visual variability for different music genres and sounds. I discuss how StarrySwarm, my implementation of BOIDS, was the most dynamic across movement and color and responsive to changes in sound.
Link to Image Gallery
https://youtube.com/playlist?list=PLsro6Cwvmceuaw9eLh6N0waUc08S1HUG7&si=ytggW_LJeVyFO39g
Recommended Citation
Zhou, Angela A., "STARRYSWARM: Making Art From Sound With Swarm Algorithms" (2025). Scripps Senior Theses. 2565.
https://scholarship.claremont.edu/scripps_theses/2565
Data Repository Link
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.
