DEFINING SPACES OF POTENTIAL ART The significance of representation in computer-aided creativity
Inhaltsverzeichnis
Reference
Palle Dahlstedt: DEFINING SPACES OF POTENTIAL ART The significance of representation in computer-aided creativity. In: Description and Creativity conference, King's College, Cambridge, 2005.
DOI
Abstract
One way of looking at the creative process is as a search in a space of possible answers. One way of simulating such a process is through evolutionary algorithms, i.e., simulated evolution by random variation and selection. The search space is defined by the chosen genetic representation, a kind of formal description, and the ways of navigating the space are defined by the choice of genetic operators (e.g., mutations). In creative systems, such as computer-aided music composition tools, these choices determine the efficiency of the system, in terms of the diversity of the results, the degree of novelty and the coherence within the material. Based on various implementations developed during five years of research, and experiences from real-life artistic applications, I will explain and discuss these mechanisms, from a perspective of the creative artist.
Extended Abstract
Bibtex
Used References
P.Dahlstedt. Creating and exploring huge parameter spaces: interactive evolution as a tool for sound generation
P. Dahlstedt. In A. Schloss, R. Dannenberg and P. Driessen (eds.), Proceedings of International Computer Music Conference 2001, pp.235--242. Havana, Cuba: Instituto Cubano de la Musica, and San Francisco, CA: International Computer Music Association.
P. Dahlstedt and M.G.Nordahl. Augmented Creativity: Evolution of musical score material. Preprint, 2004. Co-author: Mats G. Nordahl
P. Dahlstedt. Sounds Unheard of – Evolutionary algorithms as creative tools for the contemporary composer. Doctoral thesis, Chalmers University of Technology, Göteborg, 2004.
R. Dawkins. The Selfish Gene. Oxford: Oxford University Press, 1976/1989.
Dawkins, R. (1986), The Blind Watchmaker, Harlow Logman
R. A. Garcia. Growing Sound Synthesizers using Evolutionary Methods. In Proceedings of the Sixth European Conference on Artificial Life. Workshop on Artificial Life Models for Musical Applications. Prague: Editoriale Bios, 2001.
Jeanine Graf and Wolfgang Banzhaf, Interactive Evolution of Images, 1995.
Lindenmayer, A. (1968), “Mathematical Models for Cellular Interaction in Development, Parts I and II”, Journal of Theoretical Biology,18, pp 280–315.
Jon McCormack: Interactive Evolution of L-System Grammars for Computer Graphics Modelling
J. B. Putnam. Genetic Programming of Music. Technical report, New Mexico Institute of Mining and Technology, 1994.
Sims, K. (1991) “Artificial Evolution for Computer Graphics”, Computer Graphics,25(4) July 1991, pp. 319–328
K. Thywissen. GeNotator: An environment for investigating the application of genetic algorithms in computer assisted composition. In Proceedings of International Computer Music Conference 1996 (ICMC96), pp.274--277, Hong Kong, 1996
K. Wehn. Using ideas from natural selection to evolve synthesized sounds. In Proceedings of the Digital Audio Effects DAFX98 workshop, Barcelona, 1998
