  We present a general computational approach that enables a machine to
generate a dance for any input music. We encode intuitive, flexible heuristics
for what a 'good' dance is: the structure of the dance should align with the
structure of the music. This flexibility allows the agent to discover creative
dances. Human studies show that participants find our dances to be more
creative and inspiring compared to meaningful baselines. We also evaluate how
perception of creativity changes based on different presentations of the dance.
Our code is available at https://github.com/purvaten/feel-the-music.
