Skip to main content

A Connectionist Architecture for the Evolution of Rhythms

  • Conference paper
Applications of Evolutionary Computing (EvoWorkshops 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3907))

Included in the following conference series:

Abstract

In this paper we propose the use of an interactive multi-agent system for the study of rhythm evolution. The aim of the model proposed here is to show to what extent new rhythms emerge from both the interaction between autonomous agents, and self-organisation of internal rhythmic representations. The agents’ architecture includes connectionist models to process rhythmic information, by extracting, representing and classifying their compositional patterns. The internal models of the agents are then explained and tested. This architecture was developed to explore the evolution of rhythms in a society of virtual agents based upon imitation games, inspired by research on Language evolution.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Horner, A., Goldberg, D.: Genetic algorithms and computer-assisted music composition. In: Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo, CA. Morgan Kauffman, San Francisco (1991)

    Google Scholar 

  2. Gratland-Jones, A., Copley, P.: The suitability of genetic algorithms for musical composition. Contemporary Music Review 22(3), 43–55 (2003)

    Article  Google Scholar 

  3. Griffith, N., Todd, P.: Musical Networks. MIT-Press, Cambridge (1999)

    Google Scholar 

  4. Blackmore, S.: The Meme Machine. Oxford University Press, Oxford (1999)

    Google Scholar 

  5. Gimenes, M., Miranda, E.R., Johnson, C.: A memetic approach to the evolution of rhythms in a society of software agents. In: Proceedings of the 10th Brazilian Symposium of Musical Computation (SBCM), Belo Horizonte (Brazil) (2005)

    Google Scholar 

  6. Horowitz, D.: Generating rhythms with genetic algorithms. In: Anderson, P., Warwick, K. (eds.) Proceedings of the International Computer Music Conference, Aarhus (Denmark). International Computer Music Association (1994)

    Google Scholar 

  7. Tokui, N., Iba, H.: Music composition with interactive evolutionary computation. In: Proc. 3rd International Conf. on Generative Art, Milan, Italy (2000)

    Google Scholar 

  8. Brown, A.R.: Exploring rhythmic automata. In: Rothlauf, F., et al. (eds.) Proceedigs of the 3rd European Workshop on Evolutionary Music and Art, Lausanne (Swizerland). Springer, Heidelberg (2005)

    Google Scholar 

  9. Coutinho, E., Gimenes, M., Martins, J., Miranda, E.R.: Computational musicology: An artificial life approach. In: Proceedings of the 2nd Portuguese Workshop on Artificial Life and Evolutionary AlgorithmsWorkshop, Covilhã (Portugal). Springer, Heidelberg (2005)

    Google Scholar 

  10. Miranda, E., Todd, P.: A-life and musical composition: A brief survey. In: Proceedings of the IX Brazilian Symposium on Computer Music, Campinas (Brazil) (2003)

    Google Scholar 

  11. Steels, L.: The synthetic modeling of language origins. Evolution of Communication 1(1), 1–34 (1997)

    Article  Google Scholar 

  12. Werner, G., Todd, P.: Too many love songs: Sexual selection and the evolution of communication. In: Husbands, P., Harvey, I. (eds.) ECAL 1997, pp. 434–443. MIT Press, Cambridge (1997)

    Google Scholar 

  13. Miranda, E.R.: Emergent sound repertoires in virtual societies. Computer Music Journal 26(2), 77–90 (2002)

    Article  Google Scholar 

  14. Wittgenstein, L.: Philosophical Investigations. Blackwell Publishers, Malden (1979)

    Google Scholar 

  15. Steels, L.: A self-organizing spatial vocabulary. Artificial Life 2(3), 319–332 (1995)

    Article  Google Scholar 

  16. de Boer, B.: Self-Organisation in Vowel Systems. PhD thesis, Vrije Universiteit Brussel AI-lab (1999)

    Google Scholar 

  17. Reck Miranda, E.: Mimetic development of intonation. In: Anagnostopoulou, C., Ferrand, M., Smaill, A. (eds.) ICMAI 2002. LNCS (LNAI), vol. 2445, p. 107. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  18. Haykin, S.: Neural Networks. Prentice Hall, New Jersey (1999)

    MATH  Google Scholar 

  19. James, D.L., Miikkulainen, R.: SARDNET: a self-organizing feature map for sequences. In: Tesauro, G., Touretzky, D., Leen, T. (eds.) Advances in Neural Information Processing Systems, vol. 7, pp. 577–584. MIT Press, Cambridge (1995)

    Google Scholar 

  20. Bosma, M.: Musicology in a virtual world: A bottom up approach to the study of musical evolution. Master’s thesis, University of Groningen (2005)

    Google Scholar 

  21. Kohonen, T.: Self-Organizing Maps. Springer Series in Information Sciences. Springer, Heidelberg (1997)

    MATH  Google Scholar 

  22. Bednar, J.A., Miikkulainen, R.: Joint maps for orientation, eye, and direction preference in a self-organizing model of V1. Neurocomputing (2006) (in press)

    Google Scholar 

  23. Rosenblatt, F.: Principles of neurodynamics: Perceptrons and the theory of brain mechanisms. Spartan Books, Washington (1962)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Martins, J.M., Miranda, E.R. (2006). A Connectionist Architecture for the Evolution of Rhythms. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_66

Download citation

  • DOI: https://doi.org/10.1007/11732242_66

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33237-4

  • Online ISBN: 978-3-540-33238-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics