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

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Guide to Computing for Expressive Music Performance

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Abstract

This chapter introduces an imitative multi-agent system approach to generate expressive performances of music, based on agents’ individual parameterized musical rules. We have developed a system called IMAP (imitative multi-agent performer). Aside from investigating the usefulness of such an application of the imitative multi-agent paradigm, there is also a desire to investigate the inherent feature of diversity and control of diversity in this methodology: a desirable feature for a creative application, such as musical performance. To aid this control of diversity, parameterized rules are utilized based on previous expressive performance research. These are implemented in the agents using previously developed musical analysis algorithms. When experiments are run, it is found that agents are expressing their preferences through their music performances and that diversity can be generated and controlled.

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Acknowledgments

This work was financially supported by the EPSRC-funded project “Learning the Structure of Music,” grant EP/D062934/1. Qijun Zhang was partially supported by the Faculty of Technology, University of Plymouth. An earlier version of this chapter was published in Computer Music Journal Vol. 34, No. 1, pp. 80–96. The authors thank MIT Press for permission to publish this chapter.

Author information

Authors and Affiliations

  1. Faculty of Arts, Interdisciplinary Centre for Computer Music Research, Plymouth University, Drake Circus, PL4 8AA, Plymouth, UK

    Eduardo R. Miranda, Alexis Kirke & Qijun Zhang

Authors
  1. Eduardo R. Miranda
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  2. Alexis Kirke
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  3. Qijun Zhang
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Corresponding author

Correspondence to Eduardo R. Miranda .

Editor information

Editors and Affiliations

  1. ICCMR, University of Plymouth, Smeaton Building 206, Plymouth, PL4 8AA, Devon, United Kingdom

    Alexis Kirke

  2. Computing, Communication & Electronics, University of Plymouth, Plymouth, PL4 8AA, United Kingdom

    Eduardo R. Miranda

Questions

Questions

  1. 1.

    What is evolutionary computation?

  2. 2.

    What is the difference between a genetic algorithm and a multi-agent system with imitation?

  3. 3.

    Why is the potential for diversity a desirable trait for a system generating novel expressive music performances?

  4. 4.

    What two communication functions does each agent in IMAP have?

  5. 5.

    What is the difference between the rule level and the analytics level in an IMAP agent’s evaluation function?

  6. 6.

    What are performance curves?

  7. 7.

    What four elements does an IMAP agent represent a score with?

  8. 8.

    Give one method of controlling the extent of performances’ diversity in IMAP.

  9. 9.

    What does the TempoRatio represent?

  10. 10.

    What type of sociological study does IMAP have the potential to be useful for?

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Miranda, E.R., Kirke, A., Zhang, Q. (2013). Artificial Evolution of Expressive Performance of Music: An Imitative Multi-Agent Systems Approach. In: Kirke, A., Miranda, E. (eds) Guide to Computing for Expressive Music Performance. Springer, London. https://doi.org/10.1007/978-1-4471-4123-5_4

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  • DOI: https://doi.org/10.1007/978-1-4471-4123-5_4

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4122-8

  • Online ISBN: 978-1-4471-4123-5

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