Modelling the underlying principles of human aesthetic preference in evolutionary art
Inhaltsverzeichnis
Reference
Ekárt, A., Joó, A., Sharma, D., Chalakov, S.: Modelling the underlying principles of human aesthetic preference in evolutionary art. Journal of Mathematics and the Arts 6(2-3), 107–124 (2012)
DOI
http://dx.doi.org/10.1080/17513472.2012.679489
Abstract
Our understanding of creativity is limited, yet there is substantial research trying to mimic human creativity in artificial systems and in particular to produce systems that automatically evolve art appreciated by humans. We propose here to study human visual preference through observation of nearly 500 user sessions with a simple evolutionary art system. The progress of a set of aesthetic measures throughout each interactive user session is monitored and subsequently mimicked by automatic evolution in an attempt to produce an image to the liking of the human user.
Extended Abstract
Bibtex
Used References
[1] S. Baluja, D. Pomerleau, and T. Jochem, Towards automated artificial evolution for computer-generated images, Connect. Sci. 6 (1994), pp. 325–354.
[2] G.D. Birkhoff, Aesthetic Measure, Harvard University Press, Cambridge, MA, 1933.
[3] M.A. Boden and E.A. Edmonds, What is generative art?, Digital Creativity 20 (2009), pp. 21–46.
[4] A.W. Burks, D.W. Warren, and J.B. Wright, An analysis of a logical machine using parenthesis-free notation, Math. Tables Other Aids Comput. 8 (1954), pp. 53–57.
[5] S. Colton, The Painting Fool (2007), Available at www.thepaintingfool.com
[6] S. Colton, Automatic invention of fitness functions with applications to scene generation, Lect. Notes Comput. Sci. 4974 (2008), pp. 381–391.
[7] S. Colton, M. Cook, A. Raad, Ludic considerations of tablet-based evo-art, Lect. Notes Comput. Sci. 6625, (2011), pp. 223–233.
[8] S. Colton, J. Gow, P. Torres, and P. Cairns, Experiments in Objet Trouve ́ Browsing, Proceedings of the First Conference on Computational Creativity, 2010, pp. 238–247, Lisbon, Portugal.
[9] S. Colton, M. Valstar, and M. Pantic, Emotionally Aware Automated Portrait Painting, Proceedings of the 3rd International Conference on Digital Interactive Media in Entertainment and Arts (DIMEA), 2008, Athens, Greece.
[10] S. Dasgupta, C. Papadimitriou, and U. Vazirani, Algorithms, Tata McGraw-Hill, New Delhi, India, 2008.
[11] R. Dawkins, The Blind Watchmaker, Longman, New York, 1986.
[12] E. den Heier and A.E. Eiben, Comparing aesthetic measures for evolutionary art, Lect. Notes Comput. Sci. 6025 (2010), pp. 311–320.
[13] S. DiPaola and L. Gabora, Incorporating characteristics of human creativity into an evolutionary art system, Genet. Program. Evolv. Mach. 10(2) (2009), pp. 97–110.
[14] S. Draves, Electric Sheep (1999), Available at electricsheep.org
[15] A. Eka ́rt, D. Sharma, and S. Chalakov, Modelling human preference in evolutionary art, Lect. Notes Comput. Sci. 6625 (2011), pp. 303–312.
[16] D. Filonik and D. Baur, Measuring aesthetics for information visualization, 13th International Conference Information Visualisation, 2009, pp. 579–584, Barcelona, Spain.
[17] G.R. Greenfield, Computational aesthetics as a tool for creativity, Proceedings of Creativity and Cognition, 2005, pp. 232–235.
[18] G.R. Greenfield, Designing Metrics for the Purpose of Aesthetically Evaluating, Proceedings of Computational Aesthetics, 2005, pp. 151–158.
[19] G.R. Greenfield, On the Origins of the Term ‘Computational Aesthetics’, Proceedings of Computational Aesthetics, 2005, pp. 9–12.
[20] G.R. Greenfield, Generative art and evolutionary refinement, Lect. Notes Comput. Sci. 6025 (2010), pp. 291–300.
[21] F. Hemsterhuis, Lettre sur la sculpture, Quoted in Encyclopedia Britannica 11 (1946) (1769).
[22] P. Koza ́rek, Aesthetic preference research for planar periodic mosaics, Diploma thesis, Masaryk University, (2006).
[23] Y. Li and C.J. Hu, Aesthetic learning in an interctive evolutionary art system, Lect. Notes Comput. Sci. 6025 (2010), pp. 301–310.
[24] P.Machado and A. Cardoso, Computing aesthetics, Lect. Notes Comput. Sci. 1515 (1998), pp. 219–228.
[25] P. Machado and A. Cardoso, All the truth about NEvAr, Appl. Intell. (Special issue on Creative Systems) 16 (2002), pp. 101–119.
[26] P. Machado, J. Romero, A. Cardoso, and A. Santos, Partially interactive evolutionary artists, New Gener. Comput. 23 (2005), pp. 143–155.
[27] J. McCormack, Open problems in evolutionary music and art, Lect. Notes Comput. Sci. 3449 (2005), pp. 428–436.
[28] G.S. Moretti, A calculation of colours: Towards the automatic creation of graphical user interface colour schemes, Ph.D. diss, Massey University, New Zealand, 2010.
[29] A.M. Noll, The beginnings of computer art in the United States: A memoir, Leonardo 27 (1994), pp. 39–44.
[30] L. Pacioli, De divina proportione, A. Paganius Paganinus, Venice, 1509.
[31] J. Rigau, M. Feixas, and M. Sbert, Informational aesthetics measures, IEEE Comp. Graph. Appl. 28(2) (2008), pp. 24–34.
[32] B.J. Ross,W. Ralph, and H. Zong, Evolutionary image synthesis using a model of aesthetics, IEEE Congress on Evolutionary Computation, 2006, pp. 1087–1094, Vancouver, Canada.
[33] K. Sims, Artificial evolution for computer graphics, Proceedings of the 18th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1991, 25, (1991), pp. 319–328, Las Vegas, NV.
[34] T. Staudek and P. Machala, Recent exact aesthetics applications, Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH, 2002, p. 241, San Antonio, Texas, USA.
[35] G. Stiny and J. Gips, Algorithmic aesthetics: Computer models for criticism and design in the arts, University of California Press, Berkeley, CA, 1978.
[36] S. Todd and W. Latham, Evolutionary art and compu- ters, Academic Press, Orlando, FL, 1992.
[37] J.J. Ventrella, ‘Evolving the Mandelbrot set to imitate figurative art, in Design by Evolution, P.F. Hingston, C.L. Barone, and Z. Michalewicz, eds., Springer, Berlin, 2008, pp. 145–167.
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