Generative Arts and Musical Machines (W3093)

30 credits, Level 6

Autumn teaching

This module explores the creative application of generative systems in software and hardware, culminating in the creation of a robot orchestra.

Through exploring key topics of generative art (stochastic processes, rule based systems, automata, intelligent systems, physical computing, hacking, circuit bending, data art and robotic art), you will gain the necessary skills required to build your own physical or audiovisual system that contributes to the robot orchestra.

The module will base the practical work on a historical study of artistic and creative use of systems, processes and algorithms in musical composition and generative arts. Historical practices and techniques will be introduced in a mix of lectures and hands-on workshop sessions.

The module has a strong practical component. Ideas and methods will be introduced in Pure Data and Max/MSP, but you will be supported in carrying out your personal projects in a range of languages including, SuperCollider, Processing, JavaScript, Web Audio, etc.

You will also learn more advanced electronics and hardware-building using microcontrollers, such as Arduino, including the use of motors, and the Arduino audio processing audio library, Mozzie. The module's assessment is individual, but you will be working with a group of fellow students from week 4 in building a robotic band, of which your piece is a component.

Prerequisite: CMT or equivalent experience and knowledge of Max/MSP or Pure Data.


100%: Seminar


100%: Coursework (Presentation, Project)

Contact hours and workload

This module is 300 hours of work. This breaks down into 22 hours of contact time and 278 hours of independent study.

This module is running in the academic year 2019/20. We also plan to offer it in future academic years. It may become unavailable due to staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of such changes to modules at the earliest opportunity.