Musical culture is developed through descent-with-modification processes of complex knowledge about music creation, but how new creation styles evolve is not well understood. To study this problem, we conducted an artificial evolution experiment involving a population of machine-learning-based automatic composition models. These models evolved under evaluation by a large number of human listeners. We found that adaptive evolution of music styles can occur when the blending inheritance of high-dimensional statistics representing composition styles is incorporated into the generation update process. We also found a significant difference in musical preferences among listeners, depending on their musical experience. The results indicate the relevance of multi-parental transmission in the cultural evolution of music styles, a nontrivial fitness landscape of creation styles, and listeners’ diverse preferences.

This content is only available as a PDF.
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit