Introduction to Computational Creativity

Algorithms and machine learning
Advanced studies
An introduction to central concepts and models of computational creativity, to some computational creativity methods in fields such as poetry, music and images. Material will be provided in the course (original articles and slides; no text book).


11.12.2013 17.00 CK112
Year Semester Date Period Language In charge
2013 autumn 28.10-05.12. 2-2 English Hannu Toivonen


Time Room Lecturer Date
Mon 10-12 C222 Hannu Toivonen 28.10.2013-05.12.2013
Thu 10-12 C222 Hannu Toivonen 28.10.2013-05.12.2013

Exercise groups

Group: 1
Time Room Instructor Date Observe
Mon 12-14 B222 Hannu Toivonen 04.11.2013—06.12.2013

Information for international students

The course will be given in English.

Slides and homework/exercise assignments

Slides and homework/exercise assignments are added during the course to the Course Schedule tab/subpage, see its left column.


Computational creativity is the study of creative behavior by computational means. This course will introduce students to some central aspects of computational creativity: machine creativity in various fields (such as poetry, arts, music) as well as more conceptual and theoretical issues of computational creativity. An outline of the course schedule and contents is available on the Course schedule tab.

NOTE: There will be no lectures and exercises during the week 18-22 Nov. (Instead, there will be a small project work during the course, see below.)

Completing the course

The course consists of (1) lectures, (2) homework assignments and exercise sessions to present and discuss the homework, (3) a small programming project, and (4) an exam. The course is completed by carrying out the homework, the project, and by taking the course exam.

  • The homework assignments will give a maximum of 12 points in total.
  • The project will give a maximum of 12 points.
  • The course exam will give a maximum of 36 points. (The exam date and place is provisionally 11 Dec 2013 at 17:00, room CK112. Check here.)

To pass the course, at least 30 points are required in total.

Alternatively, the course can be taken by a separate exam.

The course is given colloboratively by Hannu Toivonen, Alessandro Valitutti, Oskar Gross, and Jukka Toivanen.

Literature and material

The course material consists of a number of original articles and of lecture slides. Pointers to slides and homework/exercise assignments are on the Course Schedule tab/subpage.

The articles, below, are classified to two groups. (1) The mandatory material constitutes the core content of the course. Students are assumed to study all the mandatory material, and it will be covered in the exam. (2) Elective material contains useful additional information and can be used to deepen the knowledge in the area.

Some of the articles may be accessible only from university IP addresses. (VPN or http proxy may be needed to get a suitable IP if downloading articles e.g. from home.)

Topic Mandatory Material Elective Material




  • Marvin Minsky: Why people think computers can't. The AI Magazine 3(4) 3-15, 1982. (pdf)
  • Creativity as search:
    Geraint A. Wiggins: A preliminary framework for description, analysis and comparison of creative systems. Knowledge-Based Systems 19 (7): 449–458, 2006. (pdf)
  • The FACE model:
    Alison Pease and Simon Colton: Computational creativity theory: Inspirations behind the FACE and the IDEA models. 2nd International Conference on Computational Creativity (ICCC), pp. 72-77, México City, 2011. (pdf)
  • Creative autonomy, social creativity:
    K.E. Jennings: Developing creativity: Artificial barriers in artificial intelligence. Minds and Machines 20(4): 489-501, 2011. (pdf)
  • Creative autonomy, social creativity:

    R. Saunders and J.S. Gero. Artificial creativity: A synthetic approach to the study of creative behaviour. In JS Gero and ML Maher (eds), Computational and Cognitive Models of Creative Design V, Key Centre of Design Computing and Cognition, University of Sydney, Sydney, 113-139, 2001.






  • H. Manurung, G. Ritchie, H. Thompson: Towards a computational model of poetry generation. Proceedings of AISV Symposium on Creative and Cultural Aspects and Applications of AI and Cognitive Science, 79-86, 2000. (pdf)


Visual Creativity
  • Processing language overview (website)
  • Simon Colton. Automatic invention of fitness functions with application to scene generation. Applications of Evolutionary Computing. Springer Berlin Heidelberg, 2008. 381-391. (pdf)
  • M.A. Boden and E.A. Edmonds. What is Generative Art? Digital Creativity, 20(1-2):21-46, 2009. (pdf)
  • P. Galanter. Generative Art after Computers. Proceedings of the 15th International Conference on Generative Art, December, Lucca, Italy, 2012. (pdf)
  • David Norton, Derrall Heath, and Dan Ventura. Finding creativity in an artificial artist. The Journal of Creative Behavior 47 (2): 106-124, 2013. (pdf)
  • C. Reas and Ben Fry. Processing: A Programming Handbook for Visual Designers and Artists, MIT Press, 2007.
  • Graeme Ritchie. A closer look at creativity as search. Proceedings of the Third International Conference on Computational Creativity (ICCC), pp. 41-48, Dublin, Ireland, 2012.


Musical Creativity


  • G. Papadopoulos and G Wiggins: AI methods for algorithmic composition: A survey, a critical view and future prospects. AISB Symposim on Musical Creativity, 110-117, 1999. (pdf)
  • K. Binsted, A. Nijholt, O. Stock, C. Strapparava, G. Ritchie, R. Manurung, H. Pain, A. Waller, and D. O'Mara. Computational Humor. IEEE Intelligent Systems, 21(2):59-69, 2006. (pdf)
  • A. Nijholt (Ed.). Proceedings of the Third International Workshop on Computational Humor, Amsterdam, June 2012. (pdf)
  • Graeme Ritchie. Can computers create humor? AI Magazine, 30(3), 2009. (pdf)
  • (Veale 2011a): T. Veale. Creative Language Retrieval: A Robust Hybrid of Information Retrieval and Linguistic Creativity. In Proc. of the ACL’2011, the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Portland, Oregon, USA, June 19-24, 2011. (pdf)
  • (Veale 2011b): T. Veale. Creative Introspection and Knowledge Acquisition: Learning about the world thru introspective questions and exploratory metaphors. In Proc. of AAAI’2011, the 25th Conference of the Association for the Advancement of Artificial Intelligence, San Francisco, August 2011.
  • Pablo Gervás: Computational Approaches to Storytelling and Creativity. AI Magazine 30: 49–62. 2009. (pdf)
Evaluation of Machine Creativity
  • Graeme Ritchie. Some Empirical Criteria for Attributing Creativity to a Computer Program. Minds and Machines, 17(1):76-99, Springer, 2007. (pdf)
  • A. Jordanous. Evaluating Evaluation: Assessing Progress in Computational Creativity Research. Proceedings of the Second International Conference on Computational Creativity, pp. 108-110, Mexico City, 2011. (pdf)
  • Simon Colton. Creativity Versus the Perception of Creativity in Computational Systems. Proceedings of the AAAI Spring Symposium on Creative Intelligent Systems, Stanford, California, March 2008. (pdf)
  • Graeme Ritchie. Evaluating quality in creative systems. Lecture given at the Autumn School on Computational Creativity, Porvoo, Finland, November 2013. (slides)
  • Graeme Ritchie. The profile of a creative program. Lecture given at the Autumn School on Computational Creativity, Porvoo, Finland, November 2011. (slides)
Other elective material
  • Simon Colton and Geraint A. Wiggins: Computational Creativity: The Final Frontier? In ECAI 2012 - 20th European Conference on Artificial Intelligence, 21-26, Montpellier, France, August 2012.(pdf)