CEC Theses and Dissertations

Date of Award

2011

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Computer Information Systems (DCIS)

Department

Graduate School of Computer and Information Sciences

Advisor

Maxine S Cohen

Committee Member

Sumitra Mukherjee

Committee Member

Maria Niederberger

Abstract

When genetic algorithms (GA) are used to produce music, the results are limited by a fitness bottleneck problem. To create effective music, the GA needs to be thoroughly trained by humans, but this takes extensive time and effort. Applying online collective intelligence or "crowdsourcing" to train a musical GA is one approach to solve the fitness bottleneck problem. The hypothesis was that when music was created by a GA trained by a crowdsourced group and music was created by a GA trained by a small group, the crowdsourced music would be more effective and musically sound. When a group of reviewers and composers evaluated the music, the crowdsourced songs scored slightly higher overall than the songs from the small-group songs, but with the small number of evaluators, the difference was not statistically significant.

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