Generative Arts and Musical Machines (W3093)
30 credits, Level 6
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.
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%: Practical (Workshop)
100%: Coursework (Portfolio, Project)
Contact hours and workload
This module is approximately 300 hours of work. This breaks down into about 22 hours of contact time and about 278 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to COVID-19, staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.
This module is offered on the following courses: