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



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.


Preference Weight Music Performance Agent Preference Musical Score Preference Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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.


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Eduardo R. Miranda
    • 1
  • Alexis Kirke
    • 1
  • Qijun Zhang
    • 1
  1. 1.Faculty of ArtsInterdisciplinary Centre for Computer Music Research, Plymouth UniversityPlymouthUK

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