Artificial Evolution of Expressive Performance of Music: An Imitative Multi-Agent Systems Approach

As early as the 1950s and early 1960s, pioneers such as Lejaren Hiller, Gottfried Michael Koenig, Iannis Xenakis, and Pietro Grossi, among a few others, started to gain access to computers to make music. It soon became clear that to render music with a socalled “human feel,” computers needed to process information about performance (e.g., deviations in tempo and loudness), in addition to the symbols that are normally found in a traditional musical score (e.g., pitch and rhythm). This was especially relevant for those interested in using the computer to play back scores. Indeed, the first ever attempt at creating a computer-music programming language, by Max Mathews at Bell Telephone Laboratories in 1957, was motivated by his wish to “write a program to perform music on the computer” (Park 2009 p. 10). It appears that this development began after Mathews and John Pierce went to a piano concert together. During the intermission, Pierce suggested that perhaps a computer could perform as well as the pianist. Mathews took up the challenge, which resulted in Music I, the ancestor of music programming languages such as Csound (Boulanger 2000). Research into computational models of expressive performance of music (Widmer and Goebl 2004) is still an active area of study—particularly, research into devising increasingly more sophisticated automated and semi-automated computer systems for expressive music performance, hereinafter referred to as CSEMP. A CSEMP is able to generate expressive performances of music. For example, software for music typesetting is often used to write a piece of music, but most packages play back the music in a