Abstract
In this paper we introduce the concept of a progressive percussion graph as a musical space and the metaphor of composition as the musical expression of a traveling experience in that space. A Progressive Percussion Graph is a directed graph where each node is associated with a particular percussion rhythm and each connection corresponds to a rhythmic progression, generated through optimization processes, from one percussion rhythm to another, respecting the connections direction. We have explored different optimization techniques and different path-finding algorithms resulting in a rich and diverse musical output.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Biles, J., Genjam: A genetic algorithm for generating jazz solos. In: Proceedings of the International Computer Music Conference, pages 131 (1994)
Brown, A.R., Wooller, R.W., Kate, T.: The Morph Table: A collaborative interface for musical interaction. Australiasian Computer Music Association (2007)
Burton, A.R., Vladimirova, T.R.: Generation of musical sequences with genetic techniques. Computer Music Journal 23(4), 59–73 (1999)
Croes, G.A.: A method for solving traveling-salesman problems. In: Operations Research, pp. 791–812 (1958)
Dahlstedt, P.: Autonomous evolution of complete piano pieces and performances. In: Proceedings of Music AL Workshop (2007)
Hoover, A., Stanley, K.: Exploiting functional relationships in musical composition. Connection Science (2), 227–251 (2009)
Horner, A., Goldberg, D.: Genetic algorithms and computer assisted music composition. In: Proceedings of the Fourth International Conference on Genetic Algorithms, pp. 437–441 (1991)
Horowitz, D.: Generating rhythms with genetic algorithms. In: Proceedings Of The National Conference On Artificial Intelligence, pp. 1459–1459. John Wiley & Sons Ltd. (1995)
Johanson, B., Poli, R.: GP-Music: An Interactive Genetic Programming System for Music Generation with Automated Fitness Raters. In: Proceedings of the Third Annual Conference: Genetic Programming, pp. 181–186 (1998)
Koza, J.R.: On the programming of computers by means of natural selection, vol. 1. MIT Press (1996)
Miranda, E.R., Biles, J.A.: Evolutionary Computer Music, vol. (7). Springer (2007)
Monkey machine - the online drum machine, http://rinki.net/pekka/monkey/
Percussion Walker - A Percussion Graph Prototype, http://bookmark.labmag.di.fc.ul.pt/?page_id=1966
Phon-Amnuaisuk, S., Tuson, A., and Wiggins, G. Evolving musical harmonisation. In International Conference on Adaptive and Natural Computing Algorithms, pp. 1–9 (1999)
Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn. Prentice-Hall (2003)
Smith, Joshua R.: Designing Biomorphs with an Interactive Genetic Algorithm. In Proceedings of the Fourth International Conference on Genetic Algorithms, pp. 535–538. Morgan Kaufmann Publisher (1991)
Tokui, N., Iba, H.: Music composition with interactive evolutionary computation. In: Proceedings of the 3rd International Conference on Generative Art, vol. 17, pp. 215–226 (2000)
Wooller, R., Brown, A.R.: Investigating morphing algorithms for generative music. In: Third Iteration: Third International Conference on Generative Systems in the Electronic Arts, Melbourne, Australia (2005)
Wooller, R., Brown, A.R.: Note sequence morphing algorithms for performance of electronic dance music. Digital Creativity 22(1), 13–25 (2011)
Yee-King, M.J.: The evolving drum machine. In: Music-AL Workshop, ECAL Conference (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lopes, P., Urbano, P. (2012). The Traveling Percussionist. In: Machado, P., Romero, J., Carballal, A. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2012. Lecture Notes in Computer Science, vol 7247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29142-5_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-29142-5_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29141-8
Online ISBN: 978-3-642-29142-5
eBook Packages: Computer ScienceComputer Science (R0)