Information Technology Reference
In-Depth Information
exploit the generative nature of ecosystem processes. While ecosystemic methods
don't offer a “magic bullet” in terms of searching the creative Klondike spaces of
any generative system, they do make it easier to at least begin to conceptualise and
design systems capable of high creative reward. As the complexity and sophistica-
tion of ecosystem artworks develop, we are likely to see further advances in the new
creatively made possible with computers that use this approach.
Acknowledgements This research was supported by Australian Research Council Discovery
Grants DP0877320 and DP1094064.
References
Aunger, R. (2002). The electric meme: a new theory of how we think . New York: Free Press.
Baluja, S., Pomerleau, D., & Jochem, T. (1994). Simulating user's preferences: towards automated
artificial evolution for computer generated images. Connection Science , 6 , 325-354.
Basalla, G. (1998). The evolution of technology . Cambridge: Cambridge University Press.
Begon, M., Townsend, C., & Harper, J. (2006). Ecology: from individuals to ecosystems .New
York: Wiley-Blackwell.
Bell, S. (1999). Landscape: pattern, perception and process . London: E & F N Spon.
Bentley, P. J., & Corne, D. W. (Eds.) (2002). Creative evolutionary systems . London: Academic
Press.
Bird, J., Husbands, P., Perris, M., Bigge, B., & Brown, P. (2008). Implicit fitness functions
for evolving a drawing robot. In M. Giacobini et al. (Eds.), Lecture notes in computer sci-
ence: Vol. 4974 . Applications of evolutionary computing, EvoWorkshops 2008: EvoCOMNET,
EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Proceed-
ings , Naples, Italy, March 26-28, 2008 (pp. 473-478). Berlin: Springer.
Birkhoff, G. D. (1933). Aesthetic measure . Cambridge: Harvard University Press.
Boden, M. A. (2010). Creativity and art: three roads to surprise . London: Oxford University Press.
Bown, O., & McCormack, J. (2010). Taming nature: tapping the creative potential of ecosystem
models in the arts. Digital Creativity , 21 (4), 215-231. http://www.csse.monash.edu.au/~jonmc/
resources/DC2010/ .
Brown, D. E. (1991). Human universals . New York: McGraw-Hill.
Dahlstedt, P. (2006). A mutasynth in parameter space: interactive composition through evolution.
Organised Sound , 6 (2), 121-124.
Dawkins, R. (1999). The extended phenotype: the long reach of the gene (rev. ed.). Oxford: Oxford
University Press.
De Landa, M. (2000). A thousand years of nonlinear history . Cambridge: MIT Press.
Di Scipio, A. (2003). 'Sound is the interface': from interactive to ecosystemic signal processing.
Organised Sound , 8 (3), 269-277.
Dissanayake, E. (1995). Homo aestheticus: where art comes from and why . Seattle: University of
Washington Press.
Dorin, A. (2001). Aesthetic fitness and artificial evolution for the selection of imagery from the
mythical infinite library. In J. Kelemen & P. Sosík (Eds.), LNAI: Vol. 2159 . Advances in ar-
tificial life (pp. 659-668). Prague: Springer. http://www.csse.monash.edu.au/~aland/PAPERS/
aestheticFitness_ECAL2001.pdf .
Driessens, E., & Verstappen, M. (2008). Natural processes and artificial procedures. In P. F.
Hingston, L. C. Barone & Z. Michalewicz (Eds.), Natural computing series . Design by evo-
lution: advances in evolutionary design (pp. 101-120). Berlin: Springer.
Dutton, D. (2002). Aesthetic universals. In B. Gaut & D. M. Lopes (Eds.), The Routledge compan-
ion to aesthetics . London: Routledge. http://www.denisdutton.com/universals.htm .
Search WWH ::




Custom Search