Towards models of user preferences in interactive musical evolution

We describe the "bottom-up" construction of a system which aims to build models of human musicalpreferences with strong predictive power. We use Grammatical Evolution to construct models from toydatasets which mimic real-world user-generated data. These models will ultimately substitute for the subjective fitness functions that human users employ during Interactive Evolution of melodies.