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The Art of Artificial Evolution pp 417–451Cite as

Facing the Future: Evolutionary Possibilities for Human-Machine Creativity

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Part of the Natural Computing Series book series (NCS)

Summary

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.

Keywords

  • 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.

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Authors and Affiliations

  1. Centre for Electronic Media Art Monash University, Clayton, Victoria 3800, Australia

    Jon McCormack

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  1. Jon McCormack
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Editors and Affiliations

  1. Department of Information and Communication Technologies, University of A Coruña Campus de Elvina, 15071 La Coruña, Spain

    Juan Romero

  2. CISUC Dept. of Informatics Engineering, University of Coimbra, 3030 Coimbra, Portugal

    Penousal Machado

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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

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  • DOI: https://doi.org/10.1007/978-3-540-72877-1_19

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