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Genetic Improvisation Model A Framework for Real-Time Performance Environments

Part of the Lecture Notes in Computer Science book series (LNCS,volume 2611)

Abstract

This paper presents the current state in an ongoing development of the Genetic Improvisation Model (GIM): a framework for the design of real-time improvisational systems. The aesthetic rationale for the model is presented, followed by a discussion of its general principles. A discussion of the Emonic Environment, a networked system for audiovisual creation built on GIM’s principles, follows.

Keywords

  • Recurrent Neural Network
  • Complex Adaptive System
  • Emergent Behavior
  • Experimental Music
  • Aesthetic Criterion

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.

Not following one fixed aesthetic idiom, such as a particular music style.

Here, global criteria define what constitutes an overall good improvisation, while local criteria are those of an immediate context.

From here on improvisation & any derivative words refer to the non-idiomatic improvisation.

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© 2003 Springer-Verlag Berlin Heidelberg

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Nemirovsky, P., Watson, R. (2003). Genetic Improvisation Model A Framework for Real-Time Performance Environments. In: , et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_50

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  • DOI: https://doi.org/10.1007/3-540-36605-9_50

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00976-4

  • Online ISBN: 978-3-540-36605-8

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