Algorithmic Composition by Autonomous Systems with Multiple Time-Scales
This work addresses algorithmic composition for music generation, presenting an incremental approach to achieving variation in autonomous systems.
The paper tackles algorithmic composition by integrating sound and score synthesis into monolithic autonomous systems with multiple time-scales, using strategies like slow-fast dynamics and statistical feedback, as illustrated in a case study.
Dynamic systems have found their use in sound synthesis as well as score synthesis. These levels can be integrated in monolithic autonomous systems in a novel approach to algorithmic composition that shares certain aesthetic motivations with some work with autonomous music systems, such as the search for emergence. We discuss various strategies for achieving variation on multiple time-scales by using slow-fast, hybrid dynamic systems, and statistical feedback. The ideas are illustrated with a case study.