This chapter examines the possibilities and challenges that lie ahead for evolutionary music and art. Evolutionary computing methods have enabled new modes of creative expression in the art made by humans. One day, it may be possible for computers to make art autonomously. The idea of machines making art leads to the question: what do we mean by ‘making art’ and how do we recognise and acknowledge artistic creativity in general? Two broad categories of human-machine creativity are defined: firstly, machines that make art like, and for, humans; and secondly, machines that make ‘art’ that is recognised as creative and novel by other machines or agents. Both these categories are examined from an evolutionary computing perspective. Finding ‘good’ art involves searching a phase-space of possibilities beyond astronomical proportions, which makes evolutionary algorithms potentially suitable candidates. However, the problem of developing artistically creative programs is not simply a search problem. The multiple roles of interaction, environment, physics and physicality are examined in the context of generating aesthetic output. A number of ‘open problems’ are proposed as grand challenges of investigation for evolutionary music and art. For each problem, the impetus and background are discussed. The paper also looks at theoretical issues that might limit prospects for art made by machines, in particular the role of embodiment, physicality and morphological computation in agent-based and evolutionary models. Finally, the paper looks at artistic challenges for evolutionary music and art systems.
- Pixel Image
- Golden Ratio
- Artistic Creativity
- Evolutionary Computing
- Creative Behaviour
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Tax calculation will be finalised at checkout
Purchases are for personal use onlyLearn about institutional subscriptions
Unable to display preview. Download preview PDF.
Dreyfus, H.L., Dreyfus, S.E., Athanasiou, T. (1986). Mind Over Machine: The Power of Human Intuition and Expertise in the Era of the Computer. Free Press. New York
Whitelaw, M. (2004). Metacreation: Art and Artificial Life. MIT Press. Cambridge, Mass.
Cohen, H. (1995). The further exploits of Aaron, painter. Stanford Humanities Review, 4: 141–158
Cohen, H. (1999). Colouring without seeing: A problem in machine creativity
McCormack, J. (2005). Open problems in evolutionary music and art. In Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G., eds.: Applications of Evolutionary Computing, EvoWorkshops 2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, and EvoSTOC. Vol. 3449 of Lecture Notes in Computer Science. Lausanne, Switzerland. Springer, 428–436
Carey, J. (2005). What Good are the Arts? Faber and Faber Limited. London
Dissanayake, E. (1988). What is Art For? University of Washington Press. Seattle
Dissanayake, E. (1995). Homo Aestheticus: Where Art Comes From and Why. University of Washington Press. Seattle
Miller, G.F. (2000). The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature. William Heinemann. London
Partridge, D., Rowe, J. (2002). Creativity: A computational modeling approach. In Dartnall, T., ed.: Creativity, Cognition, and Knowledge: An Interaction. Praeger, 211–238
Humphrey, N.K. (1973). The illusion of beauty. Perception, 2: 429–439
Dartnall, T., ed. (2002). Creativity, Cognition, and Knowledge: An Interaction. Praeger. Westport, Connecticut
Wolpert, D.H., Macready, W.G. (1997). No free lunch theorems for search. IEEE Transactions on Evolutionary Computation, 1(1): 67–82
Langton, C.G. (1989). Artificial life. In Langton, C.G., ed.: Artificial Life. Vol. 6 of SFI Studies in the Sciences of Complexity. Addison-Wesley, 1–47
Pattee, H.H. (1988). Simulations, realizations, and theories of life. In Langton, C.G., ed.: Artificial Life. Vol. VI. Addison-Wesley, 63–77
Bonabeau, E.W., Theraulaz, G. (1994). Why do we need artificial life? Artificial Life, 1: 303–325
Dennett, D.C. (1995). Darwin’s Dangerous Idea: Evolution and the Meanings of Life. Simon & Schuster. New York
Borges, J.L. (1970). The library of babel. In Yates, D.A., Irby, J.E., eds.: Labyrinths. Penguin Books. Harmondsworth
Dennett, D.C. (1991). Real patterns. Journal of Philosophy, 88: 27–51
Berlyne, D.E. (1971). Aesthetics and Psychobiology. Appleton-Century-Crofts. New York, N.Y.
Allison, L. (2002). Model Classes. Technical Report 2002/125. School of Computer Science and Software Engineering, Monash University. Clayton, Victoria, Australia
Sims, K. (1991). Artificial evolution for computer graphics. Computer Graphics, 25(4): 319–328
Takagi, H. (2001). Interactive evolutionary computation: Fusion of the capabilities of ec optimization and human evaluation. Proceedings of the IEEE, 89: 1275–1296
Dorin, A. (2001). Aesthetic fitness and artificial evolution for the selection of imagery from the mythical infinite library. In Kelemen, J., Sosík, P., eds.: Advances in Artificial Life. Vol. 2159 of LNAI. Prague. Springer, 659–668
Eiben, A.E., Smith, J.E. (2003). Introduction to Evolutionary Computing. Natural Computing Series. Springer
McCormack, J. (2002). Evolving for the audience. International Journal of Design Computing, 4 Available on-line: http://www.arch.usyd.edu.au/kcdc/journal/vol4/index.html.
Kitano, H. (1990). Designing neural networks using genetic algorithms with graph generation system. Complex Systems, 4: 461–476
Birkhoff, G.D. (1933). Aesthetic Measure. Harvard University Press. Cambridge, MA
Scha, R., Bod, R. (1993). Computational aesthetics. Informatie en Informatiebeleid, 11: 54–63
Elam, K. (2001). Geometry of Design: Studies in Proportion and Composition. Number 107 in Design briefs. Princeton Architectural Press. New York, N.Y.
Thompson, D.W. (1942). On Growth and Form. 2nd edn. Cambridge University Press. Cambridge
Douady, S., Couder, Y. (1992). Phyllotaxis as a physical self-organized growth process. Phys. Rev. Lett., 68: 2098–2101
Douady, S., Couder, Y. (1996). Phyllotaxis as a dynamical self organizing process (part i, ii, iii). Journal of Theoretical Biology, 139: 178–312
Doczi, G. (1981). The Power of Limits: Proportional Harmonies in Nature, Art and Architecture. Shambhala (Distributed by Routledge & Kegan Paul). London
Bringhurst, R. (1992). The Elements of Typographic Style. Second edition edn. Hartley & Marks. Vancouver, BC
Holger, H. (1997). Why a special issue on the golden section hypothesis?: An introduction. Empirical Studies of the Arts, 15
Kemp, M. (2004). Divine proportion and the holy grail. Nature, 428: 370
Tufte, E.R. (2006). Beautiful Evidence. Graphics Press LLC. Cheshire, Connecticut
Manaris, B., Machado, P., McCauley, C., Romero, J., Krehbiel, D. (2005). Developing fitness functions for pleasant music: Zipf’s law and interactive evolution systems. In Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G., eds.: Applications of Evolutionary Computing, EvoWorkshops 2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, and EvoSTOC. Vol. 3449 of Lecture Notes in Computer Science. Lausanne, Switzerland. Springer, 489–507
Taylor, R.P., Micolich, A.P., Jonas, D. (1999). Fractal analysis of Pollock’s drip paintings. Nature, 399: 422
Ramachandran, V.S., Hirstein, W. (1999). The science of art: A neurological theory of aesthetic experience. Journal of Consciousness Studies, 6: 15–51
Ramachandran, V.S. (2003). The Emerging Mind. Reith lectures. BBC in association with Profile Books. London
Rooke, S. (2002). Eons of genetically evolved algorithmic images. In Bentley, P.J., Corne, D.W., eds.: Creative Evolutionary Systems. Academic Press. London, 339–365
Wheeler, M. (2005). Reconstructing the Cognitive World: The Next Step. MIT Press. Cambridge, Mass.
Pfeifer, R., Bongard, J. (2006). How the Body Shapes the Way We Think: A New View of Intelligence. MIT Press. Cambridge, MA
Hornby, G.S., Pollack, J.B. (2001). Evolving l-systems to generate virtual creatures. Computers & Graphics, 26: 1041–1048
Sims, K. (1994). Evolving virtual creatures. In: Computer Graphics. ACM SIGGRAPH, 15–22
Dorin, A. (2007). A survey of virtual ecosystems in generative electronic art. In Romero, J., Machado, P., eds.: The Art of Artificial Evolution. Springer
Taylor, T. (2002). Creativity in evolution: Individuals, interactions, and environments. In Bentley, P.J., Corne, D.W., eds.: Creative Evolutionary Systems. Academic Press. London, 79–108
Brown, D.E. (1991). Human Universals. McGraw-Hill. New York
Berlekamp, E.R., Conway, J.H., Guy, R.K. (1982). Winning Ways for your Mathematical Plays. Vol. 2. Academic Press. New York
Nake, F. (1994). How far away are we from the first masterpiece of computer art? In Brunnstein, K., Raubold, E., eds.: IFIP 13th World Congress 94. Vol. 2. Elsevier Science, B.V.. North-Holland, 406–413
Clark, A. (2003). Natural-Born cyborgs: Minds, Technologies, and the Future of Human Intelligence. Oxford University Press. New York
Levin, G. (2000). Painterly Interfaces for Audiovisual Performance. Master of science thesis in media arts and sciences. MIT. Boston
Eldridge, A.C. (2005). Cyborg dancing: Generative systems for man-machine musical improvisation. In Innocent, T., ed.: Proceedings of Third Iteration. CEMA. Melbourne, 129–141
Packard, N.H. (1988). Intrinsic adaption in a simple model for evolution. In Langton, C.G., ed.: Artificial Life. Los Alamos, NM. Addison-Wesley, 141–155
Partridge, D., Rowe, J. (1994). Computers and Creativity. Intellect. Oxford, England
Boden, M.A. (1994). What is creativity? In Boden, M.A., ed.: Dimensions of Creativity. MIT Press. Cambridge, MA, 75–117
Saunders, R., Gero, J.S. (2001). Artificial creativity: A synthetic approach to the study of creative behaviour. In Gero, J.S., ed.: Proceedings of the Fifth Conference on Computational and Cognitive Models of Creative Design. Sydney. Key Centre of Design Computing and Cognition, 113–139
Bird, J. (2004). Containing Reality: Epistemological Issues in Generative Art and Science. In: Impossible Nature: The Art of Jon McCormack. Australian Centre for the Moving Image, 40–53
Emmeche, C., Køppe, S., Stjernfelt, F. (1997). Explaining emergence: Towards an ontology of levels. Journal for General Philosophy of Science, 28: 83–119
Bedau, M.A., McCaskill, J.S., Packard, N.H., Rasmussen, S., Adami, C., Green, D., Ikegami, T., Kaneko, K., Ray, T.S. (2000). Open problems in artificial life. Artificial Life, 6: 363–376
Abelson, H., DiSessa, A.A. (1982). Turtle Geometry: The Computer as a Medium for Exploring Mathematics. The MIT Press series in artificial intelligence. MIT Press. Cambridge, Mass.
Bird, J., Stokes, D. (2006). Evolving minimally creative robots. In Colton, S., Pease, A., eds.: Proceedings of The Third Joint Workshop on Computational Creativity (ECAI 06), 1–5
Editors and Affiliations
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
McCormack, J. (2008). Facing the Future: Evolutionary Possibilities for Human-Machine Creativity. In: Romero, J., Machado, P. (eds) The Art of Artificial Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72877-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72876-4
Online ISBN: 978-3-540-72877-1