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.
Bibliographical noteThis is an electronic version of an article published in Ekárt, A. , Joó, A., Sharma, D., & Chalakov, S. (2012). Modelling the underlying principles of human aesthetic preference in evolutionary art. Journal of mathematics and the arts, 6(2-3), 107-124. Journal of mathematics and the arts is available online at: www.tandfonline.com/10.1080/17513472.2012.679489
- aesthetic measure
- human preference modelling
- evolutionary art
- genetic programming
- interactive versus automatic evolution