Article

Choreogenetics: the generation of choreographic variants through genetic mutations and selection

Author:

François-Joseph LapointeAuthors Info & Claims

GECCO '05: Proceedings of the 7th annual workshop on Genetic and evolutionary computation

Pages 366 - 369

https://doi.org/10.1145/1102256.1102338

Published: 25 June 2005 Publication History

Abstract

In this paper, a genetic algorithm is introduced to generate variants of a choreographic sequence, which are then selected using different criteria. The mutation phase of the algorithm applies six types of mutations on single sequences, as well as four types of mutations on multiple sequences. Six different selection criteria are also distinguishable to assess the fitness of the sequences. An application of Choreogenetics is presented to illustrate the performance of the method for the generation of an aesthetic choreography.

References

[1]

Biles, J. A. GenJam in perspective: a tentative taxonomy for GA music and art systems. Leonardo, 36, 1 (2003), 43--45.

[2]

Birkhoff, G. D. Aesthetic Measure. Harvard University Press, Cambridge, MA, 1933.

[3]

Bradley, E., and Stuart, J. Using chaos to generate variations on movement sequences. Chaos, 8 (1998), 800--807.

[4]

Burton, A. R., and Vladimirova, T. Generation of musical sequences with genetic techniques. Comput. Music J., 23 (1999), 59--73.

Digital Library

[5]

Hagendoorn, I. Cognitive dance improvisation: how study of the motor system can inspire dance (and vice versa). Leonardo, 36, 3(2003), 221--227.

[6]

Jukes T. H., and Cantor C. R. Evolution of protein molecules. In Mammalian protein metabolism (ed. Munro H. N.). Academic Press, New York, NY, 1969, 21--132.

[7]

Kemp, M. The Mona Lisa of modern science. Nature, 421 (2003), 416--420.

[8]

Kimura, M. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol., 16 (1980), 111--120.

[9]

Koshelev, M., Kreinovich, V., and Yam, Y. Towards the use of aesthetics in decision making: Kolmogorov complexity formalizes Birkhoff's ideas. Bull. EATCS, 66 (1998), 166--170.

[10]

Lansdowne, J. The computer and choreography. IEEE Computer, 11 (1978), 19--30.

Digital Library

[11]

Miranda, E. R. At the crossroads of evolutionary computation and music: self-programming synthesizers, swarn orchestras and the origins of melody. Evol. Comput., 12, 2 (2004), 137--158.

Digital Library

[12]

Nelkin, D., and Anker, S. The influence of genetics on contemporary art. Nature Rev. Gen., 3 (2002), 967--971.

[13]

Ramachandran, V. S., and Hirstein, W. The science of art: a neurological theory of aesthetic experience. J. Conscious. Stud., 6 (1999), 15--51.

[14]

Romero Cardlada, J. J., and Johnson, C. Genetic algorithms in visual art and music. Leonardo, 35, 2 (2002), 175--184.

[15]

Schneider, T. D. Information content of individual genetic sequences. J. Theor. Biol., 189 (1997), 427--441.

[16]

Yan, J. F. DNA and the I Ching --The Tao of Life. North Atlantic Books, Berkeley, CA, 1991.

[17]

Zweig, J. Ars combinatoria: mystical systems, procedural art, and the computer. Art Journal, 56 (1997), 20--29.

Cited By

Hassan SDe Lacerda Pataca CNourian LTigwell GDavis BSilver Wagman W(2024)Designing and Evaluating an Advanced Dance Video Comprehension Tool with In-situ Move Identification CapabilitiesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642710(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642710
Salgaonkar ASuresh PSindhu P(2023)Automatic Mapping of BharatNAtyam Margam to Sri Chakra DanceComputer Assisted Music and Dramatics10.1007/978-981-99-0887-5_12(179-203)Online publication date: 25-Jun-2023
https://doi.org/10.1007/978-981-99-0887-5_12
Joshi MChakrabarty S(2021)An extensive review of computational dance automation techniques and applicationsProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences10.1098/rspa.2021.0071477:2251Online publication date: 7-Jul-2021
https://doi.org/10.1098/rspa.2021.0071
Show More Cited By

Index Terms

Choreogenetics: the generation of choreographic variants through genetic mutations and selection
1. Applied computing
  1. Arts and humanities

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cover image ACM Conferences

GECCO '05: Proceedings of the 7th annual workshop on Genetic and evolutionary computation

June 2005

431 pages

ISBN:9781450378000

DOI:10.1145/1102256

Conference Chair:
Franz Rothlauf
University of Mannheim, Germany

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2005

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GECCO05

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SIGEVO

GECCO05: Genetic and Evolutionary Computation Conference

June 25 - 26, 2005

D.C., Washington

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Hassan SDe Lacerda Pataca CNourian LTigwell GDavis BSilver Wagman W(2024)Designing and Evaluating an Advanced Dance Video Comprehension Tool with In-situ Move Identification CapabilitiesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642710(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642710
Salgaonkar ASuresh PSindhu P(2023)Automatic Mapping of BharatNAtyam Margam to Sri Chakra DanceComputer Assisted Music and Dramatics10.1007/978-981-99-0887-5_12(179-203)Online publication date: 25-Jun-2023
https://doi.org/10.1007/978-981-99-0887-5_12
Joshi MChakrabarty S(2021)An extensive review of computational dance automation techniques and applicationsProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences10.1098/rspa.2021.0071477:2251Online publication date: 7-Jul-2021
https://doi.org/10.1098/rspa.2021.0071
Carlson KTsang HPhillips JSchiphorst TCalvert TAlaoui SPasquier PSchiphorst TFrançoise JBevilacqua F(2015)Sketching movementProceedings of the 2nd International Workshop on Movement and Computing10.1145/2790994.2791007(68-75)Online publication date: 14-Aug-2015
https://dl.acm.org/doi/10.1145/2790994.2791007
Heidarpour MHoseini S(2015)Generating art tile patterns using genetic algorithm2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)10.1109/CFIS.2015.7391652(1-4)Online publication date: Sep-2015
https://doi.org/10.1109/CFIS.2015.7391652
Carlson KSchiphorst TDiPaola S(2014)Collaborative Choreography: A Critical Inquiry into Designing Creative Interactive SystemsIntelligent Technologies for Interactive Entertainment10.1007/978-3-319-08189-2_6(46-56)Online publication date: 2014
https://doi.org/10.1007/978-3-319-08189-2_6
Jadhav SJoshi MPawar J(2012)Art to SMart: An evolutionary computational model for BharataNatyam choreography2012 12th International Conference on Hybrid Intelligent Systems (HIS)10.1109/HIS.2012.6421365(384-389)Online publication date: Dec-2012
https://doi.org/10.1109/HIS.2012.6421365
Lewis M(2008)Evolutionary Visual Art and DesignThe Art of Artificial Evolution10.1007/978-3-540-72877-1_1(3-37)Online publication date: 2008
https://doi.org/10.1007/978-3-540-72877-1_1
Lapointe FÉpoque MZhang HChua TSteinmetz RKankanhalli MWilcox L(2005)The dancing genome projectProceedings of the 13th annual ACM international conference on Multimedia10.1145/1101149.1101276(555-558)Online publication date: 6-Nov-2005
https://dl.acm.org/doi/10.1145/1101149.1101276

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