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Genetic Algorithms

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Algorithmic Composition

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Abstract

Genetic algorithms as a particular class of evolutionary algorithms, i.e. strategies modeled on natural systems, are stochastic search techniques. The basic models were inspired by Darwin’s theory of evolution. Problem solving strategies result from the application of quasi-biological procedures in evolutionary processes. The terminology of genetic algorithms including “selection,” “mutation,” “survival of the fittest,” etc. illustrates the principles of these algorithms as well as their conceptual proximity to biological selection processes.

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References

  1. Biles JA (1994) GenJam: a genetic algorithm for generating jazz solos. In: Proceedings of the 1994 International Computer Music Conference. International Computer Music Association, San Francisco

    Google Scholar 

  2. Bile JA (1995) GenJam Populi: training an IGA via audience-mediated performance. In: Proceedings of the 1995 International Computer Music Conference. International Computer Music Association, San Francisco

    Google Scholar 

  3. Biles JA (1998) Interactive GenJam: integrating real-time performance with a genetic algorithm. In: Procedings of the 1998 International Computer Music Conference. International Computer Music Association, San Francisco

    Google Scholar 

  4. Biles JA (1999) Life with GenJam: interacting with a musical IGA. In: Proceedings of the 1999 IEEE International Conference on Systems, Man and Cybernetics, vol 3. IEEE, Piscatory, NJ, pp 652–656

    Google Scholar 

  5. Biles JA, Anderson PG, Loggi LW (1996) A neural network fitness function for a musical IGA. In: Anderson PG, Warwick K (eds) IIA’ 96/SOCO’ 96: first international ICSC symposium on intelligent industrial automation (IIA’ 96) and soft computing (SOCO’ 96). ICSC, Millet, Alberta, pp B39–B44

    Google Scholar 

  6. Burton AR (1998) A hybrid neuro-genetic pattern evolution system applied to musical composition. Dissertation, University of Surrey, 1998

    Google Scholar 

  7. Dahlstedt P, Nordahl MG (2001) Living melodies: coevolution of sonic communication. Leonardo, 34/3, 2001

    Google Scholar 

  8. Darwin C (1859) On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. John Murray, London

    Google Scholar 

  9. Dunn J, Clark MA (1999) The sonification of proteins. Leonardo, 32/1, 1999

    Google Scholar 

  10. Fels S, Manzolli J (2001) Interactive, evolutionary textured sound composition. In: Jorge JA, Correia NM, Jones H, Kamegai MB (eds) Multimedia 2001: Proceedings of the Eurographics workshop in Manchester, United Kingdom, September 8–9, 2001. Springer Wien, pp 153–164

    Google Scholar 

  11. Gartland-Jones A (2002) Can a genetic algorithm think like a composer? In: Proceedings of 5th International Conference on Generative Art, Politecnico di Milano University, Milan, 2002

    Google Scholar 

  12. Gartland-Jones A (2003) MusicBlox: a real-time algorithmic composition system incorporating a distributed interactive genetic algorithm. In: Raidl G et al (eds) Applications of evolutionary computing. Lecture notes in computer science, vol 2611. Springer, Berlin, pp 490–501

    Google Scholar 

  13. Gartland-Jones A, Copley P (2003) The suitability of genetic algorithms for musical composition. Contemporary Music Review, 22/3, 2003

    Google Scholar 

  14. Gena P, Strom C (2001) A physiological approach to DNA music. In: Proceedings of CADE 2001: the 4th Computers in Art and Design Education Conference, Glasgow, 2001

    Google Scholar 

  15. Gena P, Strom C (1995) Musical synthesis of DNA sequences. XI Colloquio di Informatica Musicale, Università di Bologna, 1995

    Google Scholar 

  16. Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison Wesley, Bonn. ISBN 0-201-15767-5

    MATH  Google Scholar 

  17. Holland J (1975) Adaption in natural and artificial systems. University of Michigan Press, Ann Arbor, Michigan

    MATH  Google Scholar 

  18. Horner A, Goldberg DE (1991) Genetic algorithms and computer-assisted music composition. In: Proceedings of the 1991 International Computer Music Conference. International Computer Music Association, San Francisco

    Google Scholar 

  19. Horowitz D (1994) Generating rhythms with genetic algorithms. In: Procedings of the 1994 International Computer Music Conference. International Computer Music Association, San Francisco

    Google Scholar 

  20. Jacob BL (1994) Composing with genetic algorithms. In: Proceedings of the 1994 International Computer Music Conference. International Computer Music Association, San Francisco

    Google Scholar 

  21. Jacob BL (1996) Algorithmic composition as a model of creativity. Organised Sound, 1/3, December, 1996

    Google Scholar 

  22. Johanson B (1997) Automated fitness raters for the GPMusic system. Masters Degree Final Project, University of Birmingham, 1997

    Google Scholar 

  23. Johanson B, Poli R (1998) GP-Music: an interactive genetic programming system for music generation with automated fitness raters. In: Koza JR et al (eds) Genetic programming 1998. Morgan Kaufmann, San Francisco

    Google Scholar 

  24. Koza JR (1992) Genetic programming: on the programming of computers by means of natural selection. MIT Press, Cambridge, Mass. ISBN 0-262-11170-5

    MATH  Google Scholar 

  25. Manzolli JA, Moroni F, Von Zuben R, Gudwin R (1999) An evolutionary approach applied to algorithmic composition. In: Proceedings of SBC99-XIX National Congress of the Computation Brazilian Society, Rio de Janeiro, 3, 1999

    Google Scholar 

  26. Mc Intyre RA (1994) Bach in a Box: the evolution of four part Baroque harmony using the genetic algorithm. In: Proceedings of the First IEEE Conference on Evolutionary Computation, Orlando, Florida, 1994, vol 2. IEEE, Piscataway, NJ, pp 852–857

    Google Scholar 

  27. Miranda ER, Biles JA (eds) (2007) Evolutionary computer music. Springer, London. ISBN 13 978-1-84628-599-8

    Google Scholar 

  28. Moroni A, Manzolli J, Von Zuben F (2000) Composing with interactive genetic algorithms. In: Proceedings of SBC2000 — Congresso da Sociedade Brasileira de Computação, 2000

    Google Scholar 

  29. Papadopoulos G, Wiggins G (1998) A genetic algorithm for the generation of jazz melodies. STeP98, Jyväskylä, Finland, 1998

    Google Scholar 

  30. Pazos A, Santos A, Dorado J, Romero-Cardalda JJ (1999) Adaptative aspects of rhythmic composition: Genetic Music. In: Banzhaf W (ed) GECCO’ 99: proceedings of the Genetic and Evolutionary Computation Conference, vol 2. Morgan Kaufmann, San Francisco

    Google Scholar 

  31. Pazos A, Romero-Cardalda JJ, Santos A, Dorado J (1999) Genetic Music Compositor. In: Proceedings of 1999 Congress on Evolutionary Computation, vol 2. IEEE, Piscataway, NJ. pp 885–890

    Google Scholar 

  32. Pearce M (2000) Generating rhythmic patterns: a combined neural and evolutionary approach. Dissertation, Department of Artificial Intelligence, University of Edinburgh, 2000

    Google Scholar 

  33. Phon-Amnuaisuk S, Tuson A, Wiggins G (1999) Evolving musical harmonisation. In: Dobnikar A, Steele NC, Pearson DW Albrecht RF (eds) Artificial neural nets and genetic algorithms: proceedings of the International Conference in Portoroz, Slovenia, 1999. Springer, Wien, pp 229–234

    Google Scholar 

  34. Phon-Amnuaisuk S, Wiggins GA (1999) The four-part harmonisation problem: a comparison between genetic algorithms and a rule-based system. In: Proceedings of the AISB’ 99 Symposium on Musical Creativity. Society for the Study of Artificial Intelligence and Simulation of Behaviour, Edinburgh

    Google Scholar 

  35. Pigg P (2002) Cohesive music generation with genetic algorithms. http://web.umr.edu/tauritzd/courses/cs401/fs2002/project/Pigg.pdf Cited 11 Nov 2004

    Google Scholar 

  36. Rechenberg I (1973) Evolutionsstrategie — Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzboog, Stuttgart

    Google Scholar 

  37. Santos A, Arcay B, Dorado J, Romero J, Rodriguez J (2000) Evolutionary computation systems for musical composition. In: Mastorakis NE (ed) Mathematics and computers in modern science. World Scientific and Engineering Society Press, Athens. ISBN 960 8052 238

    Google Scholar 

  38. Seebach G (2004) Evolutionsstrategien. http://www.seebachs.de/Evolutionsstrategien.html Cited 4 Mar 2005

    Google Scholar 

  39. Spector L, Alpern A (1994) Criticism, culture, and the automatic generation of artworks. In: Proceedings of the Twelfth National Conference on Artificial Intelligence. American Association for Artificial Intelligence, Menlo Park, Calif

    Google Scholar 

  40. Spector L, Alpern A (1995) Induction and recapitulation of deep musical structure. In: Working Notes of the IJCAI-95 Workshop on Artificial Intelligence and Music

    Google Scholar 

  41. Spector L (1995) Evolving control structures with automatically defined macros. In: Working Notes of the AAAI Fall Symposium on Genetic Programming. American Association for Artificial Intelligence, Menlo Park, Calif

    Google Scholar 

  42. Todd PM, Werner GM (1998) Frankensteinian methods for evolutionary music composition. In: Griffith N, Todd PM (eds) Musical networks: parallel distributed perception and performance. MIT Press/Bradford Books, Cambridge, Mass. ISBN 0262071819

    Google Scholar 

  43. Towsey M, Brown A, Wright S, Diederich J (2001) Towards melodic extension using genetic algorithms. Education Technology & Society, 4/2, 2001

    Google Scholar 

  44. Werner GM, Todd PM (1997) Too many love songs: sexual selection and the evolution of communication. In: Husbands, P, Harvey I (eds) (1997) Fourth European Conference on Artificial Life. MIT Press/Bradford Books, Cambridge, Mass. ISBN 0262581574

    Google Scholar 

  45. Wiggins G, Papadopoulos G, Phon-Amnuaisuk S, Tuson A (1999) Evolutionary methods for musical composition. International Journal of Computing Anticipatory Systems, 1999

    Google Scholar 

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(2009). Genetic Algorithms. In: Algorithmic Composition. Springer, Vienna. https://doi.org/10.1007/978-3-211-75540-2_7

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