Site Network: Cognitive Systems | SFB/TR 8 Spatial Cognition | Fachbereich 03 | Universität Bremen

Creativity in Cognitive Systems - WS 2017/18

Course 03-ME-711.15

Ana-Maria Olteteanu

Winter 2017/18
Thursdays 14:00 - 16:00h, Cartesium 0.01
2 SWS (ECTS: 4)


How are humans creative? How can machines be creative?
This seminar on the interdisciplinary field of Creativity in Cognitive Systems, aims to answer such questions, by blending state of the art topics and methods from the study of human creative cognition and computational creativity. In the field of human creative cognition, various types of creative cognitive processes and types of knowledge representation are discussed. In the field of computational creativity, we explore systems in the domains of mathematics and physics, drawing and painting, poetry and language, and even magic trick making. We then learn about how such cognitive systems are assessed, and examine systems which blend cognitive and computational goals.


A Introduction

1) 19 Oct 2017:

  • Introduction to Creativity in Cognitive Systems; Distribution of topics for the presentations

B Human Creative Cognition

2) 26 Oct 2017:

3) 02 Nov 2017:

4) 09 Nov 2017:

  • Representations and structure: frames, schemata, scripts, image schemas, analogical representations, mental models (Mandler, 1992)

C Computational creativity systems

5) 16 Nov 2017:

6) 23 Nov 2017:

7) 30 Nov 2017:

8) 07 Dec 2017:

D Evaluation

9) 14 Dec 2017:

10) 21 Dec 2017

E Cognitive-computational Blends

11) 11 Jan 2018:

12) 18 Jan 2018:

13) 25 Jan 2018

F Summary

14) 01 Feb 2018:

  • Final discussion

References – in order of appeareance during seminar

  • Batchelder, W. H., and Alexander, G. E. Insight problem solving: A critical examination of the possibility of formal theory. The Journal of Problem Solving 5, 1 (Fall 2012), 56-100.
  • Gentner, D. (1983). Structure‐mapping: A theoretical framework for analogy. Cognitive science, 7(2), 155-170.
  • Gentner, D., & Markman, A. B. (1997). Structure mapping in analogy and similarity. American psychologist, 52(1), 45.
  • Falkenhainer, B., Forbus, K. D., & Gentner, D. (1989). The structure-mapping engine: Algorithm and examples. Artificial intelligence, 41(1), 1-63.
  • Lakoff, G. (1990). The Invariance Hypothesis: is abstract reason based on image-schemas?. Cognitive Linguistics (includes Cognitive Linguistic Bibliography), 1(1), 39-74.
  • Mandler, J. M. (1992). How to build a baby: II. Conceptual primitives. Psychological review, 99(4), 587.
  • Langley, P., Bradshaw, G. L., & Simon, H. A. (1981, August). BACON. 5: The discovery of conservation laws. In IJCAI (Vol. 81, pp. 121-126).
  • Colton, S. (2002). The HR program for theorem generation. Automated Deduction—CADE-18, 37-61.
  • Cohen, H. (1995). The further exploits of AARON, painter. Stanford Humanities Review, 4(2), 141-158.
  • Colton, S., Valstar, M. F., & Pantic, M. (2008). Emotionally aware automated portrait painting. In Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (pp. 304-311). ACM.
  • Oliveira, H. G. (2012). PoeTryMe: a versatile platform for poetry generation. Computational Creativity, Concept Invention, and General Intelligence, 1, 21.
  • Gervás, P. (2013). Computational modelling of poetry generation. In Artificial Intelligence and Poetry Symposium, AISB Convention.
  • Williams, H., & McOwan, P. W. (2014). Magic in the machine: a computational magician's assistant. Frontiers in psychology, 5.
  • Ritchie, G., 2001, April. Assessing creativity. In Proc. of AISB’01 Symposium.
  • Gilhooly, K. J., Fioratou, E., Anthony, S. H., & Wynn, V. (2007). Divergent thinking: Strategies and executive involvement in generating novel uses for familiar objects. British Journal of Psychology, 98(4), 611-625.
  • Oltețeanu, Ana-Maria and Falomir, Zoe (2015) - comRAT-C: A Computational Compound Remote Associate Test Solver based on Language Data and its Comparison to Human Performance. In „Cognitive Systems for Knowledge Discovery”, ed. Lledó Museros, Núria Agell, and Oriol Pujol, Pattern Recognition Letters, vol. 67, pp. 81-90.
  • Oltețeanu, Ana-Maria; Schultheis, Holger and Dyer, Jonathan B. (2017) – Computationally constructing a repository of compound Remote Associates Test items in American English with comRAT-G, in: Behavior Research Methods, in press.
  • Oltețeanu, Ana-Maria (2016) - Towards an approach for computationally assisted creation of insight problems in the practical object domain, in Proceedings of the 5th International Workshop on “Computational Creativity, Concept Invention, and General Intelligence“, CEUR - Ws, vol.1767.
  • Indurkhya, B. (2016). On the role of computers in creativity-support systems. In Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions (pp. 213-227). Springer, Cham.

Course Credit

Here are a few notes on grading and other formal aspects of the course. To receive credits for the course you will need to actively and continually participate throughout the semester; this includes:
  • to read all papers;
  • to prepare 2 questions regarding each topic (based on the reading material for this topic);
  • to present at least one topic;
  • to write a term paper on either:
    • (i) the topic you presented during the course OR
    • (ii) reporting on a creative cognitive system that you designed and implemented (goals, system architecture, experiments and results).

    Here is a template for the term paper.

Questions for each topic have to be submitted by email to by the Wednesdays preceding the day when the corresponding topic is presented and discussed. Questions will be graded according to quality. For example, questions only asking for key terms explained in the reading material of the topic (e.g., "What is a Creative Cognitive System") will receive no credit. Questions should rather address conceptual issues arising from the text such as, for instance, regarding seeming contradictions or feasibility issues. Presentations should be well-prepared, well-informed, and serve to help your classmates learn about and understand the facts and issues connected with your topic and it should enable them to enter into a qualified discussion about it. Plan on a 30 - 45 min duration for your presentation and a subsequent in-depth discussions (which you will also moderate). Presentations will be graded and will account for 40% of your overall grade. Performance on questions and the term paper will account for 20% and 40% of your overall grade, respectively.

Please email your term paper to Term papers have to be submitted by 28 February 2016 the latest. Any form of plagiarism or failure to submit the term paper by the specified date will result in automatic failure of the course.