Abstract
Algorithmic music composition has long been an active area of research in computer science, but the need for a human element only recently began to be more widely acknowledged. Interactive Evolutionary Computing (IEC), made popular by Karl Sims, effectively solves many high dimension problems, like music composition, involving creative and subjective elements. This work applies several Genetic Algorithm (GA) and Genetic Programming (GP) approaches, inspired by Karl Sims, to algorithmic music composition. The implementation of these IEC algorithms is described and their effectiveness compared.
Publication Date
2006
Document Type
Master's Project
Student Type
Graduate
Department, Program, or Center
Computer Science (GCCIS)
Advisor
Geigel, Joseph
Advisor/Committee Member
Biles, John
Advisor/Committee Member
Carithers, Warren
Recommended Citation
Becker, Ryan, "Genetic music" (2006). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/6902
Campus
RIT – Main Campus
Comments
Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2013.