Autonomously Managing Competing Objectives to Improve the Creation and Curation of Artifacts

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David Norton, Derrall Heath and Dan Ventura: Autonomously Managing Competing Objectives to Improve the Creation and Curation of Artifacts. In: Computational Creativity 2014 ICCC 2014, 23-32.



DARCI (Digital ARtist Communicating Intention) is a cre- ative system that we are developing to explore the bounds of computational creativity within the domain of visual art. As with many creative systems, as we increase the auton- omy of DARCI, the quality of the artifacts it creates and then curates decreases—a phenomenon Colton and Wiggins have termed the latent heat effect. We present two new metrics that DARCI uses to evolve and curate renderings of images that convey target adjectives without completely obfuscating the original image. We show how we balance the two met- rics and then explore various ways of combining them to au- tonomously yield images that arguably succeed at this task.

Extended Abstract


author = {David Norton, Derrall Heath and Dan Ventura},
title = {Autonomously Managing Competing Objectives to Improve the Creation and Curation of Artifacts},
booktitle = {Proceedings of the Fifth International Conference on Computational Creativity},
series = {ICCC2014},
year = {2014},
month = {Jun},
location = {Ljubljana, Slovenia},
pages = {23-32},
url = {, },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},

Used References

Baluja, S.; Pomerleau, D.; and Jochem, T. 1994. Towards automated artificial evolution for computer-generated im- ages. Connection Science 6:325–354.

Bay, H.; Ess, A.; Tuytelaars, T.; and Gool, L. V. 2008. Speeded-up robust features (SURF). Computer Vision and Image Understanding 110:346–359.

Boden, M. A. 1999. Handbook of Creativity. Press Syndi- cate of the University of Cambridge. chapter 18.

Boden, M. A. 2004. The Creative Mind: Myths and Mech- anisms (second edition). Routledge.

Colton, S., and Wiggins, G. A. 2012. Computational cre- ativity: The final frontier. In 20th European Conference on Artificial Intelligence, 21–26.

Colton, S. 2008. Creativity versus the perception of creativ- ity in computational systems. Creative Intelligent Systems: Papers from the AAAI Spring Symposium 14–20.

Csurka, G.; Dance, C. R.; Fan, L.; Willamowski, J.; and Bray, C. 2004. Visual categorization with bags of keypoints. In Proceedings of the Workshop on Statistical Learning in Computer Vision, 1–22.

Datta, R.; Joshi, D.; Li, J.; and Wang, J. Z. 2006. Studying aesthetics in photographic images using a computational ap- proach. Lecture Notes in Computer Science 3953:288–301.

DiPaola, S., and Gabora, L. 2009. Incorporating character- istics of human creativity into an evolutionary art algorithm. Genetic Programming and Evolvable Machines 10(2):97– 110.

Elkan, C. 2003. Using the triangle inequality to acceler- ate k-means. In Proceedings of the Twentieth International Conference on Machine Learning, 147–153.

Fellbaum, C., ed. 1998. WordNet: An Electronic Lexical Database. The MIT Press.

Gero, J. S. 1996. Creativity, emergence, and evolution in design. Knowledge-Based Systems 9:435–448.

Gevers, T., and Smeulders, A. 2000. Combining color and shape invariant features for image retrieval. IEEE Transac- tions on Image Processing 9:102–119.

Heath, D., and Norton, D. 2009. DARCI (Digital ARtist Communicating Intention).

Heath, D.; Norton, D.; and Ventura, D. 2013. Autonomously communicating conceptual knowledge through visual art. In Proceedings of the 4th International Conference on Compu- tational Creativity, 97–104.

King, I.; Ng, C. H.; and Sia, K. C. 2004. Distributed content-based visual information retrieval system on peer- to-pear network. ACM Transactions on Information Systems 22(3):477–501.

Li, C., and Chen, T. 2009. Aesthetic visual quality assess- ment of paintings. IEEE Journal of Selected Topics in Signal Processing 3:236–252.

Machado, P.; Romero, J.; and Manaris, B. 2007. Exper- iments in computational aesthetics: An iterative approach to stylistic change in evolutionary art. In Romero, J., and Machado, P., eds., The Art of Artificial Evolution: A Hand- book on Evolutionary Art and Music. Berlin: Springer. 381– 415.

Maher, M. L.; Brady, K.; and Fisher, D. H. 2013. Com- putational models of surprise as a mechanism for evaluating creative design. In Proceedings of the 4th International Con- ference on Computational Creativity, 147–151.

Maher, M. L. 2010. Evaluating creativity in humans, com- puters, and collectively intelligent systems. In DESIRE ’10 Proceedings of the 1st DESIRE Network Conference on Cre- ativity and Innovation in Design, 22–28.

Norton, D.; Heath, D.; and Ventura, D. 2010. Establishing appreciation in a creative system. In Proceedings of the 1st International Conference on Computational Creativity, 26– 35.

Norton, D.; Heath, D.; and Ventura, D. 2011a. An artistic dialogue with the artificial. In Proceedings of the 8th ACM Conference on Creativity and Cognition, 31–40. New York, NY, USA: ACM.

Norton, D.; Heath, D.; and Ventura, D. 2011b. Au- tonomously creating quality images. In Proceedings of the 2nd International Conference on Computational Creativity, 10–15.

Norton, D.; Heath, D.; and Ventura, D. 2013. Finding cre- ativity in an artificial artist. Journal of Creative Behavior 47(2):106–124.

Ritchie, G. 2007. Some empirical criteria for attributing cre- ativity to a computer program. Minds and Machines 17:67– 99.

Sivic, J.; Russell, B. C.; Efros, A. A.; Zisserman, A.; and Freeman, W. T. 2005. Discovering objects and their location in images. International Journal of Computer Vision 1:370– 377.

Wang, W.-N.; Yu, Y.-L.; and Jiang, S.-M. 2006. Image re- trieval by emotional semantics: A study of emotional space and feature extraction. IEEE International Conference on Systems, Man, and Cybernetics 4:3534–3539.

Zujovic, J.; Gandy, L.; and Friedman, S. 2007. Identifying painting genre using neural networks. miscellaneous.


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