On virtual machine architectures for evolutionary music composition

Conference Date
2017
Location
Lyon, France
ISBN
978-0-262-34633-7
Date Published
September 2017
Conference Date: 2017, Vol. 14, Pages 577-584.
(doi: 10.7551/ecal_a_091)
© 2017 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
Article PDF (773.94 KB)
Abstract

In our ongoing work on evolutionary music composition, we explore linear genetic programming as a method of creating a virtual music composer. This process hinges on viewing the composer as a Turing-complete virtual register machine that outputs pieces of music. In this paper we compare different designs for the virtual machine, exploring various instruction sets and memory architectures; analysing their ability to create music statistically similar to that of a given corpus. We also explore different genotype sizes to see how much memory the virtual machine needs to converge to an acceptable result.