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Computational Creativity


Admission requirements

Bachelor degree (completed)


Computational Creativity is a subfield of Artificial Intelligence concerned with the philosophy, science and engineering of computational systems exhibiting behaviours that may be judged to be creative. In this course we will explore approaches to the computational modelling of creativity as well as the theories of human creativity that have informed them.

We will explore computational models of creative processes, e.g., analogy-making, models of creative individuals, e.g., creative agents, and simulations of creative societies, e.g., multi-agent models. We will explore different approaches to developing autonomous creative systems, as well as, collaborative, i.e., co-creative, systems. We will discuss fundamental questions of what it means for a machine to be creative, how computational creativity can be evaluated and the implications for human creativity.

We will read and discuss literature on human and computational creativity and gain hands-on practice with the design of a creative system, which will be demonstrated at a show-and-tell session at the end of the course.

Course objectives

This course will provide an overview of the field of computational creativity. After the successful completion of this course, you will be able to:

  • explain how computational creativity can be used in the study of human creativity;

  • recall theories of human creativity that have informed computational creativity;

  • compare different computational methods for developing models of creativity;

  • apply generative computational techniques to develop creative systems; and,

  • interpret findings from experiments with computational models of creativity.


Check MyTimetable (manual) and use your ULCN account to login. Please note that (last-minute) changes in the schedule are communicated in the course's Brightspace.

Mode of instruction

Lecture, Seminar > Pre-recorded lectures, discussion sessions, online tutorials and self study

Assessment method

Tutorials (20%)
Homework assignments (40%)
Research project (40%)

Online tutorials will accompany and expand on material covered in the lectures, completion of the tutorials is required. The homework assignments will consist of 2 graded assignments based on material covered in the tutorials. The final grade will be calculated as the weighted average of the assignments and research project.

Reading list

Study materials will be provided by the lecturer during the course.


  • You have to enrol for classes and exams (including retakes) in uSis.

  • Elective, external and exchange students (other than Media Technology and Computer Science students) need to contact the programme's coordinator due to limited capacity.


Contact the lecturer(s) for course specific questions and the programme's coordinator Barbara Visscher-van Grinsven for questions regarding the programme, admission and/or registration.