Creating Melodies With Evolving Recurrent Neural Networks (2001)
Music composition is a domain well-suited for evolutionary reinforcement learning. Instead of applying explicit composition rules, a neural network is used to generate melodies. An evolutionary algorithm is used to find a neural network that maximizes the chance of generating good melodies. Composition rules on tonality and rhythm are used as a fitness function for the evolution. We observe that the model learns to generate melodies according to these rules with interesting variations.
In Proceedings of the {INNS-IEEE} International Joint Conference on Neural Networks, pp. 2241-2246, Piscataway, NJ 2001. IEEE.

Chun-Chi Chen Undergraduate Alumni
Risto Miikkulainen Faculty risto [at] cs utexas edu