Multi-Agent Simulation for Generating Expressive Music Performance

This paper presents a system that implements a society of agent performers that evolve expressive music performances (EMP) through their interactions. Each agent performer evaluates a performance using a fitness function derived from the structure of the performing piece. Agents are born with different fitness functions, representing preferences for different types of performance. A new-born agent firstly applies a Genetic Algorithm to generate a refined performance with its fitness function. Through an agent's life, it listens to the performances of others' that it connects to in the social network. Given specific conditions, it may try imitate some performances and modify its own preference. An agent performer dies of age or inactivity. New agent performers are occasionally created. With this model, we aim to generate expressive performances through simulating the effect of social pressure and culture transmission.