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arXiv · 1910.06088

Beauty and structural complexity

Samy Lakhal·Alexandre Darmon·Jean-Philippe Bouchaud·Michael Benzaquen
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Abstract

We revisit the long-standing question of the relation between image appreciation and its statistical properties. We generate two different sets of random images well distributed along three measures of entropic complexity. We run a large-scale survey in which people are asked to sort the images by preference, which reveals maximum appreciation at intermediate entropic complexity. We show that the algorithmic complexity of the coarse-grained images, expected to capture structural complexity while abstracting from high frequency noise, is a good predictor of preferences. Our analysis suggests that there might exist some universal quantitative criteria for aesthetic judgement.

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BibTeXRIS

Samy Lakhal, Alexandre Darmon, Jean-Philippe Bouchaud, Michael Benzaquen. 2019-10-14. Beauty and structural complexity. https://doi.org/10.1103/physrevresearch.2.022058

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