Computational Creativity

6 ECTS credits
168 h study time

Offer 1 with catalog number 4022173FNR for all students in the 2nd semester at a (F) Master - specialised level.

Semester

2nd semester

Enrollment based on exam contract

Impossible

Grading method

Grading (scale from 0 to 20)

Can retake in second session

Enrollment Requirements

Students must have followed ‘Artificial Intelligence' and 'Machine Learning’ before they can enroll for ‘Computational Creativity'.

Taught in

English

Faculty

Faculty of Sciences and Bioengineering Sciences

Department

Computer Science

Educational team

Geraint Wiggins (course titular)

Activities and contact hours

26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
116 contact hours Independent or External Form of Study

Course Content

Computational Creativity has been defined (Colton and Wiggins, 2012) as

The philosophy, science and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviours that unbiased observers would deem to be creative.

Computational Creativity is the part of artificial intelligence that deals with the capacity of intelligent systems to be creative. As a field of study, it constitutes a part of AI that entails rejection of traditional representational problem-solving paradigms, and moves us back towards the study of General Intelligence.

Specifically, computational creativity accounts for the ability to imagine, to predict, to expect, and then to evaluate the results of those activities. It is a fundamental requirement of systems that aim to be truly autonomous, because it directly addresses the unpredictability of the world.

Expected course structure:

Lecture 1: Background
- Introduction to the philosophy of computational creativity; introduction to structure of module; some examples of successful computational creativity
- Lab time: reading
Lectures 2-6: Computational Creativity Theory and System Construction
- Each lecture covers material from the literature on topics such as the analysis of creative systems, the relationship between CC and AI, and so on
- Example Topics: Creative Systems Framework (Wiggins, 2006a,b); Creativity assessment of software (Ritchie, 2007); Evaluation of creative systems (Boden 1998; Jordanous, 2015)
- Lab time: individual and small group meetings for project feedback and progress discussions
Lectures 7-11: Flipped lectures on projects important topics in computational creativity.
- Each 1-hour lecture covers techniques used in the Computational Creativity literature, giving examples to inspire students to complete their module project
- Labs: 3 hours per week, in which students design, build, evaluate, and report on small computational creativity systems in an area that interests them
Lectures 12-13: Presentations of student projects
- Each student will present their project in a 15 minute oral presentation with slides, followed by 5 minutes of questions. This presentation will be assessed, and will count 10% to the total of the module. Because the final subsmission deadline is significantly later than than this point in the semester, the presentation should not include the actual evalution of the system, but it should include plans for evaluation.

Course material

Handbook (Recommended) : The Philosophy and Engineering of Autonomously Creative Systems, Veale - Cardoso, Springer, 9783319436081, 2017
Handbook (Recommended) : The Philosophy and Engineering of Autonomously Creative Systems, Veale - Cardoso, Springer E-book, 9783319436104, 2017

Additional info

Delivery will be via lecture, student-led seminar, and lab project
Representative Reading:
- Boden, M. A. (1990). The Creative Mind: Myths and Mechanisms. Weidenfield and Nicholson, London.
- Csikszentmihalyi, M. (1996). Creativity: Flow and the Psychology of Discovery and Invention. HarperCollins, New York.
- Guilford, J. (1967). The Nature of Human Intelligence. McGraw-Hill, New York.
- Koestler, A. (1976). The Act of Creation. Hutchinson, London, UK.
- Pease, A. and Colton, S. (2011). Computational creativity theory: Inspirations behind the face and idea models. In Proceedings of the International Conference on Computational Creativity.
- Wallas, G. (1926). The Art of Thought. Harcourt Brace, New York.
- Wiggins, G. A. (2006). A preliminary framework for description, analysis and comparison of creative systems. Journal of Knowledge Based Systems, 19(7):449–458.

Learning Outcomes

Algemene competenties

On successful completion of this module, you will be able to
- explain a range of philosophical approaches to human creativity
- explain the relationship between the study of human creativity and computational creativity
- explain the relationship between computational creativity and traditional AI
- explain a range of philosophical and practical approaches to computational creativity
- explain the problem of evaluation in computational creativity
- analyse and compare computational creativity systems, both autonomous and co-creative
- implement small computational creativity systems

Grading

The final grade is composed based on the following categories:
SELF Presentation determines 10% of the final mark.
SELF Practical Assignment determines 40% of the final mark.
SELF Report determines 50% of the final mark.

Within the SELF Presentation category, the following assignments need to be completed:

Presentation of CC project with a relative weight of 10 which comprises 10% of the final mark.

Within the SELF Practical Assignment category, the following assignments need to be completed:

Practical CC Project with a relative weight of 40 which comprises 40% of the final mark.

Within the SELF Report category, the following assignments need to be completed:

Report on CC project with a relative weight of 50 which comprises 50% of the final mark.

Additional info regarding evaluation

Assessment will be by course work: 1 report in the form of a conference paper, total 50%; individual project, 40%, plus peer group oral presentation, 10%.

Assessment (50%): Students will prepare a report explaining their work, in the form of a conference paper, which will be assessed for content, particularly in respect of the use of the tools and techniques presented in the module.
Assessment (10%): Students will present a 15 minute oral presentation of their project, followed by 5 minutes questions. See above for details.
Assessment (40%): Students will build a small computationally creative system and assess it as discussed in the course. Assessment here is by contiual assessment through weekly project meetings.

Because the course work is tightly integrated with the lecture materials, assessment is not available in second session for this course.

Allowed unsatisfactory mark

The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context