Composing Music with Case-Based Reasoning



Music is one of the most intriguing and joyful
domain of research and analysis. Driven by this
insatiable curiosity, Musical Analysis has
emerged to formally understand and structure
music and its intrinsic intention and causality.
Each complete analysis of a piece points to
issues that go far beyond the normal graphical
music representation. A better analysis is
important not only to a better interpretation, but
also to a more perfect composition. An
exceptional composer is indeed an exceptional
This paper presents a computational approach to
music composition through the use and
exploration of musical analysis. Centered on
Case-Based Reasoning and Planning techniques,
it consists on creating new solutions by keeping,
transforming and extrapolating knowledge from
already expert-made music analysis. For our
approach, each analysis is represented as a
precisely structured Case, divisible into all of its
The process of composition we adopt is
progressive, left-to-right, and top-to-bottom and
has some similarities with (Wallas? 1926) theory
for creative production (Macedo et al. 1996a)
which we adapted for this specifically structured
and complex domain.
The resulting implemented program has already
generated several different musical pieces, which
were examined and analyzed by experts, bringing
up precious questions and advice.


Case-Based Reasoning


AI and Music


MIND-II, September 1997

PDF File

Cited by

Year 2016 : 3 citations

 Bauer, Rouven. "A hybrid approach to supervised machine learning for algorithmic melody composition." arXiv preprint arXiv:1612.09212 (2016).

 Ramírez Moreno, Rodrigo Gabino. "Generación de música con gramáticas formales." (2016).

 Gelbukh, A. (2016). Music generation with formal grammars of multiple instruments and a conductor (Doctoral dissertation, Instituto Politécnico Nacional).

Year 2015 : 1 citations

 Mora Ángel, Fernando. "Compocyborg antroposemios: re-significación del humanismo a través de la composición musical con técnicas bio-inspiradas de inteligencia artificial." (2015).

Year 2013 : 1 citations

 Fernández, J. D., & Vico, F. (2013). AI Methods in Algorithmic Composition: A Comprehensive Survey. Journal of Artificial Intelligence Research, 48, 513-582.

Year 2012 : 2 citations

 Bertrand Bonnemason, J., Catalán Fernández, C., & Mikovski, G. (2012). Muphic: composición musical automática basada en imágenes.

 Reis, L. S., Reis, G., Barroso, J., & Pereira, A. (2012). AMIGA-An Interactive Musical Environment for Gerontechnology. Procedia Computer Science, 14, 208-217.

Year 2011 : 1 citations

 Morenoo, R. (2011). Generación de música con gramáticas formales. MSc. Thesis, Instituto Politécnico Nacional, México.

Year 2009 : 2 citations

 "Sense2: A Music System Based on Paintings", André Pintado Jorge Gonçalves, 2009, MSc Dissertation. Instituto Superior Técnico

 Nierhaus, G. (2009). Algorithmic composition paradigms of automated music generation.
Berlin: Springer.

Year 2008 : 1 citations

 "Paradigms of Automated Music Generation". Nierhaus, Gerhard. Springer. ISBN: 978-3-211-75539-6. 2008

Year 2005 : 1 citations

 Brede, Tore. "Reasoning with sequences of events in knowledge-intensive CBR." (2005).

Year 2004 : 1 citations

 Leal de Melo Daltia, Marcio. "Gerando acompanhamento rítmico automático para violão: estudo de caso do Cyber-João." (2004).

Year 2001 : 2 citations

 Dubitzky, Werner, and Francisco Azuaje. "A genetic algorithm and growing cell structure approach to learning case retrieval structures." Soft computing in case based reasoning. Springer London, 2001. 115-146.

 Colton, S., Pease, A. and Ritchie, G. "The Effect of Input Knowledge on Creativity". Proceedings of the ICCBR'01 Workshop on Creative Systems, Vancouver, Canada, 2001