response. Only after further investiga-
tion and familiarization can deficien-
cies in the work be considered.x
However, Hiller’s work and 1959
Scientific American article17 led to
much controversy and press attention.
Hostility to his achievementsy was
such that the Grove Dictionary of Music
and Musiciansz did not include an ar-
ticle on it until shortly before his death
in 1994. This hostility arose no doubt
more from a misperception of compo-
sitional practice than from anything
intrinsic to Hiller’s work.
Much of the resistance to algorithmic composition that persists to this
day stems from the misguided bias that
the computer, not the composer, composes the music. In the vast majority of
cases where the composer is also the
programmer, this is simply not true.
As composer and computer musician
Curtis Roads pointed out more than 15
x To paraphrase Ludger Brümmer, from information theory we know that new information
is perceived as chaotic or interesting but not
expressive. New information must be structured before it can be understood, and, in the
case of aesthetic experience, this structuring
involves comparison to an ideal, or an established notion of beauty. 7
y Concerning the reaction to The Illiac Suite, Hiller said “There was a great [deal] of hostility, certainly in the musical world...I was immediately
pigeonholed as an ex-chemist who had bungled
into writing music and probably wouldn’t know
how to resolve a dominant seventh chord”; interview with Vincent Plush, 1983.5
z The Grove is the English-speaking world’s
most widely used and arguably most authoritative musicological resource.
years ago, it takes a good composer to
design algorithms that result in music
that captures the imagination. 34
Furthermore, using algorithmic-composition techniques does not by necessity imply less composition work or a
shortcut to musical results; rather, it is a
change of focus from note-to-note composition to a top-down formalization of
compositional process. Composition is,
in fact, often slowed by the requirement
that musical ideas be expressed and
their characteristics encapsulated in a
highly structured and non-musical general programming language. Learning
the discipline of programming is itself
a time-consuming and, for some composers, an insurmountable problem.
Perhaps counterintuitively, such
formalization of personal composition technique allows the composer to
proceed from concrete musical or abstract formal ideas into realms hitherto
unimagined, sometimes impossible
to achieve through any other means
than computer software. As composer
Helmut Lachenmann wrote, “A composer who knows exactly what he wants,
wants only what he knows—and that is
one way or another too little.” 35 The computer can help composers overcome
recreating what they already know by
aiding more thorough investigations of
the material, once procedures are programmed, modifications and manipulations are simpler than with pencil and
paper. By “pressing buttons, introducing coordinates, and supervising the
controls,” to quote Xenakis again, 40 the
composer is able to stand back and develop compositional material en masse,
applying procedures and assessing, rejecting, accepting, or further processing
results of an often-surprising nature.
Algorithmic composition techniques
clearly further individual musical and
compositional development through
computer programming-enabled voyages of musical discovery.
1. ames, c. stylistic automata in gradient. Computer
Music Journal 7, 4 (1983), 45–56.
2. assayag, g., Bloch, g., chemillier, M., cont, a., and
Dubnov, s. oMax brothers: a dynamic topology of
agents for improvization learning. In Proceedings of the
First ACM Workshop on Audio and Music Computing
Multimedia (santa Barbara, ca). acM Press, new york,
3. austin, l., cage, J., and hiller, l. an interview with John
cage and lejaren hiller. Computer Music Journal 16, 4
4. Bel, B. Migrating musical concepts: an overview of the Bol
processor. Computer Music Journal 22, 2 (1998), 56–64.
5. Bewley, J. Lejaren A. Hiller: Computer Music Pioneer.
Music library exhibit, university of Buffalo, 2004;
6. Boulez, P. schönberg est mort. Score 6 (feb. 1952), 18–22.
7. Brümmer, l. using a digital synthesis language in
composition. Computer Music Journal 18, 4 (1994),
8. chomsky, n. Syntactic Structures. Mouton, the hague,
9. christensen, e. The Musical Timespace, a Theory of
Music Listening. aalborg university Press, aalborg,
10. cope, D. Experiments in Musical Intelligence. a-r
editions, Madison, WI, 1996.
11. ebcioglu, k. an expert system for harmonizing four-part
chorales. Computer Music Journal 12, 3 (1988), 43–51.
12. edwards, M. A Pure Data implementation of Ligeti’s
Désordre. open-source music software; http://www.
13. edwards, M. slippery chicken: A Specialized Algorithmic
Composition Program. unpublished object-oriented
common lisp software; http://www.michael-edwards.
14. edwards, M. Tramontana. sheet music, sumtone, 2004;
15. eisen, c. and keefe, s.P., eds. The Cambridge Mozart
Encyclopedia. cambridge university Press, cambridge,
16. the electronic Music foundation. HPSCHD; http://
17. hiller, l. computer music. Scientific American 201, 6
(Dec. 1959), 109–120.
18. holmes, t. Electronic and Experimental Music. taylor &
francis ltd, london, 2003.
19. howat, r. architecture as drama in late schubert. In
Schubert Studies, B. newbould, ed. ashgate Press,
london, 1998, 168–192.
20. Jordanous, a. and smaill, a. Investigating the role of
score following in automatic musical accompaniment.
Journal of New Music Research 38, 2 (2009), 197–209.
21. kinzler, h. and ligeti, g. Decision and automatism in
Désordre 1er étude, premier livre. Interface, Journal of
New Music Research 20, 2 (1991), 89–124.
22. kirchmeyer, h. on the historical construction of
rationalistic music. Die Reihe 8 (1962), 11–29.
23. koenig, g.M. Project 1; http://home.planet.nl/gkoenig/
24. koenig, g.M. aesthetic integration of computer-composer
scores. Computer Music Journal 7, 4 (1983), 27–32.
25. kramer, J. the fibonacci series in 20th century music.
Journal of Music Theory 17 (1973), 111–148.
26. kunze, t. Désordre (unpublished article); http://www.
fictive.com/t/pbl/1999 desordre/ ligeti.html
27. lendvai, e. Bela Bartók: An Analysis of His Music. kahn
& averill, london, 1971.
28. lerdahl, f. and Jackendorff, r. A Generative Theory of
Tonal Music. MIt Press, cambridge, Ma, 1983.
29. lewis, g. too many notes: computers, complexity, and
culture in Voyager. Leonardo Music Journal 10 (2000),
30. ligeti, g. Über form in der neuen musik. Darmstädter
Beiträge zur neuen Musik 10 (1966), 23–35.
31. Matossian, n. Xenakis. kahn & averill, london, 1986.
32. norden, h. Proportions in music. Fibonacci Quarterly 2,
3 (1964), 219–222.
33. Prusinkiewicz, P. and lindenmayer, a. The Algorithmic
Beauty of Plants. springer-Verlag, new york, 1990.
34. roads, c. The Computer Music Tutorial. MIt Press,
cambridge, Ma, 1996.
35. ryan, D. and lachenmann, h. composer in interview:
helmut lachenmann. Tempo 210 (1999), 20–24.
36. sowa, J. A Machine to Compose Music: Instruction Manual
for GENIAC. oliver garfield co., new haven, ct, 1956.
37. steinitz, r. Music, maths & chaos. Musical Times 137,
1837 (Mar. 1996), 14–20.
38. supper, M. a few remarks on algorithmic composition.
Computer Music Journal 25, 1 (2001), 48–53.
39. Winkler, g.e. Hybrid II: Networks. cD recording, 2003.
sumtone cd1: stryngebite; http://www.sumtone.com/
40. Xenakis, I. Formalized Music. Pendragon, hillsdale, ny,
Michael Edwards ( email@example.com) is
a reader in Music technology in the school of arts,
culture and environment of the university of edinburgh,
© 2011 acM 0001-0782/11/07 $10.00