Keele Research Repository

A variety of work has been carried out investigating the suitability of interactive genetic algorithms (IGAs) for musical composition. There have been some promising results demonstrating that it is, in principle, an effective approach. Modern sound synthesis and processing techniques (SSPTs) are often very complex and difficult to use. They often consist of tens or hundreds of parameters and a large range of values can be assigned to each parameter. This results in an immense number of parameter combinations; listening to the result of each one is clearly not viable. Furthermore, the effect each parameter has on the audio output may not be immediately obvious. Effectively using these systems can require a considerable time commitment and a great deal of theoretical knowledge. This means that in many cases these techniques are not being used to their full potential.
IGAs offer a solution to this problem by providing a user with a simpler, more accessible interface to a range of SSPTs. This allows the user to navigate more effectively through the parameter space and explore the range of materials which can be generated by an SSPT.
This thesis presents compositions and software that investigate a range of approaches to the application of IGAs to sound design, composition and performance. While investigating these areas, the aim has been to overcome the limitations of previous IGA based systems and extend this approach into new areas. A number of IGA based systems have been developed which allow a user to develop varied compositions consisting of diverse and complex material with minimal training.