6 ECTS credits
168 u studietijd

Aanbieding 1 met studiegidsnummer 4022173FNR voor alle studenten in het 2e semester met een gespecialiseerd master niveau.

Semester
2e semester
Inschrijving onder examencontract
Niet mogelijk
Beoordelingsvoet
Beoordeling (0 tot 20)
2e zittijd mogelijk
Neen
Inschrijvingsvereisten
Students must have followed ‘Artificial Intelligence' and 'Machine Learning’ before they can enroll for ‘Computational Creativity'.
Onderwijstaal
Engels
Faculteit
Faculteit Wetenschappen en Bio-ingenieurswetensch.
Verantwoordelijke vakgroep
Computerwetenschappen
Onderwijsteam
Geraint Wiggins (titularis)
Onderdelen en contacturen
26 contacturen Hoorcollege
26 contacturen Werkcolleges, practica en oefeningen
116 contacturen Zelfstudie en externe werkvormen
Inhoud

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.
Studiemateriaal
Handboek (Aanbevolen) : The Philosophy and Engineering of Autonomously Creative Systems, Veale - Cardoso, Springer, 9783319436081, 2017
Handboek (Aanbevolen) : The Philosophy and Engineering of Autonomously Creative Systems, Veale - Cardoso, Springer E-book, 9783319436104, 2017
Bijkomende 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.
Leerresultaten

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

Beoordelingsinformatie

De beoordeling bestaat uit volgende opdrachtcategorieën:
ZELF Presentatie bepaalt 10% van het eindcijfer

ZELF Praktijkopdracht bepaalt 40% van het eindcijfer

ZELF Verslag bepaalt 50% van het eindcijfer

Binnen de categorie ZELF Presentatie dient men volgende opdrachten af te werken:

  • Presentation of CC project met een wegingsfactor 10 en aldus 10% van het totale eindcijfer.

Binnen de categorie ZELF Praktijkopdracht dient men volgende opdrachten af te werken:

  • Practical CC Project met een wegingsfactor 40 en aldus 40% van het totale eindcijfer.

Binnen de categorie ZELF Verslag dient men volgende opdrachten af te werken:

  • Report on CC project met een wegingsfactor 50 en aldus 50% van het totale eindcijfer.

Aanvullende info mbt evaluatie

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.

 
 
 
Toegestane onvoldoende
Kijk in het aanvullend OER van je faculteit na of een toegestane onvoldoende mogelijk is voor dit opleidingsonderdeel.

Academische context

Deze aanbieding maakt deel uit van de volgende studieplannen:
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Artificiële Intelligentie
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Multimedia
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Software Languages and Software Engineering
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Data Management en Analytics
Master in Applied Sciences and Engineering: Computer Science: Artificial Intelligence (enkel aangeboden in het Engels)
Master in Applied Sciences and Engineering: Computer Science: Multimedia (enkel aangeboden in het Engels)
Master in Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering (enkel aangeboden in het Engels)
Master in Applied Sciences and Engineering: Computer Science: Data Management and Analytics (enkel aangeboden in het Engels)