Adaptation of an Autonomous Creative Evolutionary System for Real-World Design Application Based on Creative Cognition
Inhaltsverzeichnis
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, pp 40-4, 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
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.
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Links
Full Text
http://ivizlab.sfu.ca/papers/iccc2013.pdf
