Project Title: Evolutionary Algorithms for Creative Music Design
Student: Yanyan Zhang
Course: Bsc Hons Computer Science and Management

Abstract:
This project aims to enable users to combine two pieces of music and 
then to apply some methodologies from evolutionary algorithms (EAs) 
to evolve the two combined musical works. As general music composition 
mostly depends on users. subjectivity, a particular EA technique 
called interactive genetic algorithms (IGA), which is regarded as an 
advanced genetic algorithm (GA), is exploited. It possesses the 
characteristic of interacting with users. That is, users can evaluate 
a musical piece directly according to their preference. That evaluation 
represents a fitness value assigned to that musical piece. Other than 
the direct interaction, IGA adopts the same operators as GA. Once two 
musical pieces are merged, separate them every 4 bars as a chromosome. 
Then randomly select some chromosomes as initial population. Apply GA 
operators, which are crossover and mutation, to that initial population. 
Repeat above steps until certain end conditions are satisfied. Randomly 
pick out 16 chromosomes as phrases for users to evaluate. Return users 
evaluation to the system and then more iteration can be carried out. 
Finally, a musical piece that satisfies users most can be acquired.
Besides the demonstration of the main implementation of the project, 
this paper will also provide the literature review of EA, GA, IGA, 
some related work, and so on. Also, sections such as project motivation, 
system requirements, and testing are displayed to give a more detailed 
illustration to this project.