The Education of the AI Composer: Automating Musical Creativity

Models of computational creativity promise to provide insight into the nature of human creative work and innovation. Intrinsically motivated, automated, creative agents present a potential avenue for the exploration of creativity in the arts, and in music in particular. A novel reinforcement learning agent designed to improvise music in a self-motivated fashion is described, formulated to prove the capabilities of an artificially creative musical system. The prototype employs unsupervised adaptive resonance theory algorithms to model theories of human perception, cognition, and creativity. While the generated results are constrained for initial evaluation further extensions suggest the potential to create meaningful, aesthetically valuable compositions.