The relevance of universal metrics in relation to human aesthetic perception

A computational aesthetics model developed for the game of international chess showed a good and positive correlation with human player aesthetic assessment. The unique approach taken here suggests that, in addition to things like personal taste and environmental factors, humans also likely assess beauty based on `universal metrics' within the domain itself. From the standpoint of artificial intelligence (AI), this means that weights for aesthetic features need not, for example, be determined by analyzing a particular data set of aesthetically-rated objects, or through consultation with human experts. Instead, certain metrics can be used as `building blocks' to formalize aesthetic principles or features in a logical and dynamic way. This is arguably an improvement over existing methods. The aesthetics model developed is explained and relevant experimental results are presented. The importance of universal metrics in the aesthetics of chess and other domains is also explored.