Entropy and optimality in abstract art: an empirical test of visual aesthetics

How can aesthetic responses to artworks be computed? Previous authors have proposed governing properties, including symmetry and complexity, along with equations for quantifying these properties and combining them into an overall measure of aesthetics. But existing mathematical models have not been well motivated by psychological theories or well validated by empirical testing. An alternative model is derived here, using a novel measure of visual entropy to quantify graphic complexity and compute aesthetic optimality. This model is tested against human judgments of complexity and aesthetics using abstract designs composed of horizontal and vertical grid lines. The empirical results support the mathematical model of entropy and optimality, but also highlight difficulties associated with computing aesthetics for other abstract and figurative artworks. Implications of the data and model are discussed with regard to current and future efforts in the field of computational aesthetics, aimed at automating the evaluation of aesthetics and generation of artworks.