Cyborg Dancing: Generative Systems for Man-machine Musical Improvisation

One of the major motivating forces in generative art is the desire to explore uncharted spaces, to create artefacts that escape the designer’s control: to attain emergence. This paper focuses on the design of digital systems that would be suitable partners for man-machine collaborative exploration of these spaces. Limitations of existing approaches that impede the artist/user’s creative explorations are reviewed. The central problem is framed as a constraint on the variety of outcomes that are possible. Taking inspiration from existing musical practices, an alternative approach is proposed and illustrated with a working example of a generative man-machine system for improvised musical performance. The principle difference between this and many other digital generative artistic tools is that whereas the material from which the final artefact is made is usually defined, here it is provided in real time by the performer. This appears to increase the creative freedom of the user, whilst preserving the independence of the digital generative process and offers a practical alternative to the slippery concept of creative emergence in increasing the variability of possible artistic artefacts.

[1]  Jon McCormack,et al.  Open Problems in Evolutionary Music and Art , 2005, EvoWorkshops.

[2]  Jon Bird,et al.  The Blurring of Art and ALife , 2001 .

[3]  Mitchell Whitelaw,et al.  Metacreation: Art and Artificial Life , 2004 .

[4]  Kenneth E. Rinaldo Technology Recapitulates Phylogeny: Artificial Life Art , 1998 .

[5]  Paul Layzell,et al.  Hardware evolution : on the nature of artificially evolved electronic circuits , 2001 .

[6]  Jon McCormack,et al.  Impossible Nature: The Art of Jon McCormack , 2004 .

[7]  Alan Dorin,et al.  Aesthetic Fitness and Artificial Evolution for the Selection of Imagery from the Mythical Infinite Library , 2001, ECAL.

[8]  Kenneth L. Artis Design for a Brain , 1961 .

[9]  Golan Levin Painterly interfaces for audiovisual performance , 2000 .

[10]  P. Cariani Some epistemological implications of devices which construct their own sensors and effectors , 2000 .

[11]  J. Biles Autonomous GenJam : Eliminating the Fitness Bottleneck by Eliminating Fitness , 2022 .

[12]  John A. Biles,et al.  GenJam: A Genetic Algorithm for Generating Jazz Solos , 1994, ICMC.

[13]  Phil Husbands,et al.  Towards Epistemically Autonomous Robots: Exploiting the Potential of Physical Systems , 2003, Leonardo.

[14]  R. Dawkins The Blind Watchmaker , 1986 .

[15]  John S. McCaskill,et al.  Open Problems in Artificial Life , 2000, Artificial Life.

[16]  Mats G. Nordahl,et al.  Living Melodies: Coevolution of Sonic Communication , 2001, Leonardo.

[17]  Mark A. Bedau,et al.  Is Echo a Complex Adaptive System? , 2000, Evolutionary Computation.

[18]  Eduardo Reck Miranda On the Music of Emergent Behavior: What Can Evolutionary Computation Bring to the Musician? , 2003, Leonardo.

[19]  Stephen Todd,et al.  Evolutionary Art and Computers , 1992 .