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Computational Aesthetic Evaluation: Past and Future

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Abstract

Human creativity typically includes a self-critical aspect that guides innovation towards a productive end. This chapter offers a brief history of, and outlook for, computational aesthetic evaluation by digital systems as a contribution towards potential machine creativity. First, computational aesthetic evaluation is defined and the difficult nature of the problem is outlined. Next, a brief history of computational aesthetic evaluation is offered, including the use of formulaic and geometric theories; design principles; evolutionary systems including extensions such as coevolution, niche construction, agent swarm behaviour and curiosity; artificial neural networks and connectionist models; and complexity models. Following this historical review, a number of possible contributions towards future computational aesthetic evaluation methods are noted. Included are insights from evolutionary psychology; models of human aesthetics from psychologists such as Arnheim, Berlyne, and Martindale; a quick look at empirical studies of human aesthetics; the nascent field of neuroaesthetics; new connectionist computing models such as hierarchical temporal memory; and computer architectures for evolvable hardware. Finally, it is suggested that the effective complexity paradigm is more useful than information or algorithmic complexity when thinking about aesthetics.

Keywords

  • Artificial Neural Network
  • Fitness Function
  • Field Programmable Gate Array
  • Dynamic Time Warping
  • Niche Construction

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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Fig. 10.1
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Acknowledgements

My interest in writing this chapter began at the “Computational Creativity: An Interdisciplinary Approach” seminar in July of 2009 at the Schloss Dagstuhl—Leibniz Center for Informatics. I would like to thank Margaret Boden, Mark d’Inverno and Jon McCormack for organising the seminar. In addition my thanks go to my fellow members of the “Evaluation” discussion group at the seminar including Margaret Boden, David Brown, Paul Brown, Harold Cohen, and Oliver Deussen. Finally I enjoyed and appreciated the lively post-seminar e-mail discussion of related topics with David Brown, Paul Brown, Harold Cohen, Jon McCormack, and Frieder Nake. Please note, however, that any matters of opinion or error in this chapter are purely my own.

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Galanter, P. (2012). Computational Aesthetic Evaluation: Past and Future. In: McCormack, J., d’Inverno, M. (eds) Computers and Creativity. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31727-9_10

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