NetNeg: A Hybrid System Architecture for Composing Polyphonic Music

There are musical activities in which we are faced with symbolic and sub-symbolic processes. This research focuses on the question whether integrating a neural network together with a distributed artificial intelligence approach has any advantages in the music domain. In this work, we present a new approach for composing and analyzing poliphonic music. As a case study, we began experimenting with first species two-part counterpoint melodies. Our system design is inspired by the cognitive process of a human musician. We have developed a hybrid system composed of a connectionist module and an agent-based module to combine the symbolic and sub-symbolic levels to achieve this task. The network produces aesthetic melodies based on the training examples it was given. The agents choose which are the next notes in the two-part melodies by negotiating over the possible combinations of notes suggested by the network. Keywords: Music, Distributed Artificial Intelligence, Neural Networks, Learni..