Adaptation of an Autonomous Creative Evolutionary System for Real-World Design Application Based on Creative Cognition

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Reference

Steve DiPaola, McCaig R., Carson K., Salevati S., & Sorenson N.: Adaptation of an Autonomous Creative Evolutionary System for Real-World Design Application Based on Creative Cognition. In: Proc. International Conference on Computational Creativity Computational Creativity 2013 ICCC 2013, pp 40-47, 2013.

DOI

Abstract

This paper describes the conceptual and implementation shift from a creative research-based evolutionary system to a real-world evolutionary system for professional de- signers. The initial system, DarwinsGaze, is a Creative Genetic Programing system based on creative cognition theories. It generated artwork that 10,000’s of viewers perceived as human-created art, during its successful run at peer-reviewed, solo shows at noted museums and art galleries. In an effort to improve the system for use with real-world designers, and with multi-person creativity in mind, we began working with a noted design firm explor- ing potential uses of our technology to support multi- variant creative design iteration. This second generation system, titled Evolver, provides designers with fast, unique creative options that expand beyond their habitual selections that can be inserted/extracted from the system process at any time for modular use at varying stages of the creative design process. We describe both systems and the design decisions to adapt our research system, whose goal was to incorporate creativity automatically within its algorithms, to our second generation system, which attempts to take elements of human creativity theo- ries and populate them as tools back into the process. We report on our study with the design firm on the adapted system’s effectiveness.

Extended Abstract

Bibtex

@inproceedings{
author = {Steve DiPaola, McCaig R., Carson K., Salevati S., & Sorenson N.},
title = {Adaptation of an Autonomous Creative Evolutionary System for Real-World Design Application Based on Creative Cognition},
editor = {Simon Colton, Dan Ventura, Nada Lavrač, Michael Cook},
booktitle = {Proceedings of the Fourth International Conference on Computational Creativity},
series = {ICCC2013},
year = {2013},
month = {Jun},
location = {Sydney, New South Wales, Australia},
pages = {40-47},
url = {http://www.computationalcreativity.net/iccc2013/download/iccc2013-dipaola-et-al.pdf, http://de.evo-art.org/index.php?title=Adaptation_of_an_Autonomous_Creative_Evolutionary_System_for_Real-World_Design_Application_Based_on_Creative_Cognition },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},
}

Used References

Ashmore, L., and Miller, J. 2004. Evolutionary Art with Cartesian Genetic Programming. Technical Online Report. http://www.emoware.org/evolutionary_art.asp.

Bentley, P., and Corne, D. eds. 2002. Creative Evolution- ary Systems, San Francisco, CA.: Morgan Kaufmann.

Boden, M. 2003. The Creative Mind. London: Abacus.

Brown, J. 2009. Looking at Darwin: portraits and the mak- ing of an icon. Isis. Sept, 100(3):542–70.

Dartnell, T. 1993. Artificial intelligence and creativity: An introduction. Artificial Intelligence and the Simulation of Intelligence Quarterly 85.

DiPaola, S. and Gabora, L. 2007. Incorporating character- istics of human creativity into an evolutionary art algo- rithm. In (D. Thierens, Ed.), Proc Genetic and Evol Com- puting Conf , 2442– 2449. July 7-11, Univ College London.

Feist, G.J, 1999. The influence of personality on artistic and scientific creativity, in Handbook of Creativity, R.J. Sternberg, Ed. (Cambridge University Press, Cambridge, UK)

Gabora, L. 2000. Toward a theory of creative inklings. In (R. Ascott, Ed.) Art, Technology, and Consciousness, In- tellect Press, Bristol, UK.

Gabora, L. 2002. The beer can theory of creativity, in (P. Bentley and D. Corne, Eds.) Creative Evolutionary Sys- tems, 147-161. San Francisco, CA.: Morgan Kaufmann.

Gabora, L.2002. Cognitive mechanisms underlying the creative process. In (T. Hewett and T. Kavanagh, Eds.) Proceedings of the Fourth International Conference on Creativity and Cognition, Oct 13-16, UK, 126-133.

Gabora, L. 2005.Creative thought as a non-Darwinian evo- lutionary process. Journal of Creative Behavior, 39(4), 6587.

Gabora, L. 2010. Revenge of the “neurds”: Characterizing creative thought in terms of the structure and dynamics of memory. Creativity Research Journal, 22(1), 1-13.

Gabora, L., and DiPaola, S. 2012. How did humans be- come so creative? Proceedings of the International Confer- ence on Computational Creativity, 203-210. May 31 - June 1, Dublin, Ireland.

Harik, G. R., Lobo, F. G., and Sastry, K. 2006. Linkage Learning via Probabilistic Modeling in the Extended Com- pact Genetic Algorithm (ECGA). In D. M. Pelikan, K. Sastry, & D. E. CantúPaz (Eds.), Scalable Optimization via Probabilistic Modeling, 39–61. Springer Berlin Heidelberg.

Jennings, K. E. 2010. Developing creativity: Artificial bar- riers in artificial intelligence. Minds and Machines, 1– 13.

Koza, J R., Keane, M A., and Streeter, M J. 2003. Evolving inventions. Scientific American. February. 288(2) 52 – 59.

Lawson, B. 2006. How designers think: the design process demystified (4th Edition). Oxford: Elsevier.

Luo, J., and Knoblich, G. 2007. Studying insight with neu- roscientific methods. Methods, 42, 77-86.

Machado, P., Nunes, H., & Romero, J. 2010. Graph-Based Evolution of Visual Languages. In C. D. Chio, A. Braba- zon, G. A. D. Caro, M. Ebner, M. Farooq, A. Fink, N. Ur- quhart (Eds.), Applications of Evolutionary Computation, 271–280. Springer Berlin Heidelberg.

Miller, J. 2011. Cartesian Genetic Programming, Springer.

Miller, J., and Thomson, P. 2000. Cartesian Genetic Pro- gramming. Proceedings of the 3rd European Conference on Genetic Programming, 121-132. Edinburgh, UK.

Neisser, U. 1963. The multiplicity of thought. British Jour- nal of Psychology, 54, 1-14.

Padian, K. 2008. Darwin’s enduring legacy. Nature, 451(7179), 632–634.

Piaget, J. 1926. The Language and Thought of the Child. Routledge and Kegan Paul, London.

Pease, A. and Colton, S. 2011. On Impact and Evaluation in Computational Creativity: A Discussion of the Turing Test and an Alternative Proposal. In Proceedings of the AISB symposium on AI and Philosophy .

Rips, L. J. 2001. Necessity and natural categories. Psycho- logical Bulletin, 127(6), 827-852.

Ritchie, G. 2007. Some empirical criteria for attributing creativity to a computer program. Minds and Machines 17.

Shneiderman, B. 2007. Creativity support tools: accelerat- ing discovery and innovation. Commun. ACM, 50(12), 20– 32.

Schön, D. 1988. Designing: Rules, Types, and Worlds. Design Studies, 9/3 181-4.

Sloman, S. 1996. The empirical case for two systems of reasoning. Psychol. Bull. 9(1), 3–22.

Suwa, M., Gero, J. S., and Purcell, T. 1998. The roles of sketches in early conceptual design processes. In Proceed- ings of Twentieth Annual Meeting of the Cognitive Sci- ence Society, 1043-1048.

Walker, J. and Miller, J. 2005. Improving the Evolvability of Digital Multipliers Using Embedded Cartesian Genetic Programming and Product Reduction. Evolvable Systems: From Biology to Hardware, 6th International Conference, ICES 2005, Proceedings, Sitges, Spain. Springer.

Yu, T., and Miller, J. 2001. Neutrality and the Evolvability of Boolean function landscape. Proceedings of the Fourth European Conference on Genetic Programming, 204-217. Berlin Springer-Verlag.


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