What to expect when you’re expecting: The role of unexpectedness in computationally evaluating creativity

Proceedings of the 5th International Conference on Computational Creativity, ICCC 2014

Volumn , Issue , 2014, Pages

  Grace, Kazjon ^a   Maher, Mary Lou ^a  

^a UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL CREATIVITIES; COMPUTATIONAL MODEL; CONCEPTUAL FRAMEWORKS;

ARTIFICIAL INTELLIGENCE;

EID: 85086287849     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (36)

1. Abra, J. 1988. Assaulting Parnassus: Theoretical views of creativity. University Press of America Lanham, MD.
2. Baldi, P., and Itti, L. 2010. Of bits and wows: a bayesian theory of surprise with applications to attention. Neural Networks 23(5):649–666.
3. Berlyne, D. E. 1966. Curiosity and exploration. Science 153(3731):25–33.
4. Berlyne, D. E. 1970. Novelty, complexity, and hedonic value. Perception & Psychophysics 8(5):279–286.
5. Bishop, C. M. 1994. Novelty detection and neural network validation. In Vision, Image and Signal Processing, IEE Proceedings-, volume 141, 217–222. IET.
6. Boden, M. A. 2003. The creative mind: Myths and mechanisms. Routledge.
7. Csikszentmihalyi, M. 1988. Society, culture, and person: A systems view of creativity. Cambridge University Press.
8. Dudek, S. Z. 1993. The morality of 20th-century transgressive art. Creativity Research Journal 6(1-2):145–152.
9. Feyerabend, P. K. 1963. How to be a good empiricist: a plea for tolerance in matters epistemological. In Philosophy of science: The Delaware seminar, volume 2, 3–39. New York, Interscience Press.
10. Fisher, D. H. 1987. Knowledge acquisition via incremental conceptual clustering. Machine learning 2(2):139–172.
11. Florida, R. L. 2012. The Rise of the Creative Class: Revisited. Basic books.
12. Grace, K.; Maher, M.; Fisher, D.; and Brady, K. 2014a. A data-intensive approach to predicting creative designs based on novelty, value and surprise. International Journal of Design Creativity and Innovation (to appear).
13. Grace, K.; Maher, M.; Fisher, D.; and Brady, K. 2014b. Modeling expectation for evaluating surprise in design creativity. In Proceedings of Design Computing and Cognition, volume (to appear).
14. Horvitz, E. J.; Apacible, J.; Sarin, R.; and Liao, L. 2012. Prediction, expectation, and surprise: Methods, designs, and study of a deployed traffic forecasting service. arXiv preprint arXiv:1207.1352.
15. Itti, L., and Baldi, P. 2005. A principled approach to detecting surprising events in video. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, 631–637. IEEE.
16. Jennings, K. E. 2010. Developing creativity: Artificial barriers in artificial intelligence. Minds and Machines 20(4):489–501.
17. Macedo, L., and Cardoso, A. 2001. Modeling forms of surprise in an artificial agent. Structure 1(C2):C3.
18. Maher, M. L., and Fisher, D. H. 2012. Using ai to evaluate creative designs. In 2nd International conference on design creativity (ICDC), 17–19.
19. Maher, M. L.; Brady, K.; and Fisher, D. H. 2013. Computational models of surprise in evaluating creative design. In Proceedings of the Fourth International Conference on Computational Creativity, 147.
20. Maher, M. L. 2010. Evaluating creativity in humans, computers, and collectively intelligent systems. In Proceedings of the 1st DESIRE Network Conference on Creativity and Innovation in Design, 22–28. Desire Network.
21. Newell, A.; Shaw, J.; and Simon, H. A. 1959. The processes of creative thinking. Rand Corporation.
22. O’Quin, K., and Besemer, S. P. 1989. The development, reliability, and validity of the revised creative product semantic scale. Creativity Research Journal 2(4):267–278.
23. Ortony, A., and Partridge, D. 1987. Surprisingness and expectation failure: what’s the difference? In Proceedings of the 10th international joint conference on Artificial intelligence-Volume 1, 106–108. Morgan Kaufmann Publishers Inc.
24. Pearce, M. T.; Ruiz, M. H.; Kapasi, S.; Wiggins, G. A.; and Bhattacharya, J. 2010. Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation. NeuroImage 50(1):302–313.
25. Peters, M. 1998. Towards artificial forms of intelligence, creativity, and surprise. In Proceedings of the twentieth annual conference of the cognitive science society, 836–841. Citeseer.
26. Runco, M. A. 2010. Creativity: Theories and themes: Research, development, and practice. Access Online via Elsevier.
27. Saunders, R., and Gero, J. S. 2001a. The digital clockwork muse: A computational model of aesthetic evolution. In Proceedings of the AISB, volume 1, 12–21.
28. Saunders, R., and Gero, J. S. 2001b. Artificial creativity: A synthetic approach to the study of creative behaviour. Computational and Cognitive Models of Creative Design V, Key Centre of Design Computing and Cognition, University of Sydney, Sydney 113–139.
29. Saunders, R. 2012. Towards autonomous creative systems: A computational approach. Cognitive Computation 4(3):216–225.
30. Schmidhuber, J. 2010. Formal theory of creativity, fun, and intrinsic motivation (1990–2010). Autonomous Mental Development, IEEE Transactions on 2(3):230–247.
31. Schumpeter, J. 1942. Creative destruction. Capitalism, socialism and democracy.
32. Silberschatz, A., and Tuzhilin, A. 1995. On subjective measures of interestingness in knowledge discovery. In KDD, volume 95, 275–281.
33. Sosa, R., and Gero, J. S. 2005. A computational study of creativity in design: the role of society. AI EDAM 19(4):229–244.
34. Strzalecki, A. 2000. Creativity in design: General model and its verification. Technological Forecasting and Social Change 64(2):241–260.
35. Wiggins, G. A. 2006a. A preliminary framework for description, analysis and comparison of creative systems. Knowledge-Based Systems 19(7):449–458.
36. Wiggins, G. A. 2006b. Searching for computational creativity. New Generation Computing 24(3):209–222.