Algorithms for musical composition: A question of granularity

Abstract

Early approaches to computer-generated music are examined, and it is argued that making music is concerned with a higher level of granularity than that of the notes on music paper. Work in artificial intelligence shows that low-level decisions such as the selection of individual notes may actually be subordinate to a model-based control structure, the models being examples of how problems have been resolved. It is suggested that the search for algorithmic rules should be directed by two questions: how to identify units of material of the appropriate granularity, and, given a collection of those units, how to properly assemble them.