Skip to main content

Fitness in Evolutionary Art and Music: What Has Been Used and What Could Be Used?

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7247))

Abstract

This paper considers the notion of fitness in evolutionary art and music. A taxonomy is presented of the ways in which fitness is used in such systems, with two dimensions: what the fitness function is applied to, and the basis by which the function is constructed. Papers from a large collection are classified using this taxonomy. The paper then discusses a number of ideas that have not be used for fitness evaluation in evolutionary art and which might be valuable in future developments: memory, scaffolding, connotation and web search.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Basa, T., Go, C., Yoo, K.S., Lee, W.H.: Using physiological signals to evolve art. In: Rothlauf et al. [40], pp. 633–641

    Google Scholar 

  2. Bilotta, E., Pantano, P., Cupellini, E., Rizzuti, C.: Evolutionary methods for melodic sequences generation from non-linear dynamic systems. In: Giacobini et al. [18], pp. 585–592

    Google Scholar 

  3. Bird, J., Faith, J., Webster, A.: Tabula Rasa: A case study in evolutionary curation. In: Cagnoni et al. [6], pp. 981–995

    Google Scholar 

  4. Bird, J., Husbands, P., Perris, M., Bigge, B., Brown, P.: Implicit fitness functions for evolving a drawing robot. In: Giacobini et al. [19], pp. 473–478

    Google Scholar 

  5. Bown, O., McCormack, J.: Taming nature: tapping the creative potential of ecosystem models in the arts. Digital Creativity 21(4), 215–231 (2010)

    Article  Google Scholar 

  6. Raidl, G.R., Cagnoni, S., Cardalda, J.J.R., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G., Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.): EvoWorkshops 2003 . LNCS, vol. 2611. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  7. Colton, S.: Automatic invention of fitness functions with application to scene generation. In: Giacobini et al. [19], pp. 381–391

    Google Scholar 

  8. Colton, S., López de Mántaras, R., Stock, O.: Computational creativity: Coming of age. AI Magazine 30(3), 11–14 (2009)

    Google Scholar 

  9. Daelemans, W., van den Bosch, A.: Memory-Based Language Processing. Cambridge University Press (2005)

    Google Scholar 

  10. Dahlstedt, P.: Autonomous evolution of complete piano pieces and performances. In: Workshop on Music and Artificial Life (2007)

    Google Scholar 

  11. Dahlstedt, P., Nilsson, P.: Free flight in parameter space: A dynamic mapping strategy for expressive free impro. In: Giacobini et al. [19], pp. 479–484

    Google Scholar 

  12. Dawkins, R.: The Selfish Gene, 2nd edn., Original edition. Oxford University Press (1989)

    Google Scholar 

  13. Dawkins, R.: Climbing Mount Improbable. Penguin (1997)

    Google Scholar 

  14. Di Chio, C., Brabazon, A., Di Caro, G.A., Ebner, M., Farooq, M., Fink, A., Grahl, J., Greenfield, G., Machado, P., O’Neill, M., Tarantino, E., Urquhart, N. (eds.): EvoApplications 2010. LNCS, vol. 6025. Springer, Heidelberg (2010)

    Google Scholar 

  15. Di Chio, C., Brabazon, A., Di Caro, G.A., Drechsler, R., Farooq, M., Grahl, J., Greenfield, G., Prins, C., Romero, J., Squillero, G., Tarantino, E., Tettamanzi, A.G.B., Urquhart, N., Uyar, A.Ş. (eds.): EvoApplications 2011, Part II. LNCS, vol. 6625. Springer, Heidelberg (2011)

    Google Scholar 

  16. Evans, B.: Integration of music and graphics through algorithmic congruence. In: Proceedings of the 1987 International Computer Music Conference, pp. 17–24 (1987)

    Google Scholar 

  17. Gartland-Jones, A.: Musicblox: A real-time algorithmic composition system incorporating a distributed interactive genetic algorithm. In: Cagnoni et al. [6], pp. 145–155

    Google Scholar 

  18. Giacobini, M., et al. (eds.): EvoWorkshops 2007. LNCS, vol. 4448. Springer, Heidelberg (2007)

    Google Scholar 

  19. Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Drechsler, R., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., McCormack, J., O’Neill, M., Romero, J., Rothlauf, F., Squillero, G., Uyar, A.Ş., Yang, S. (eds.): EvoWorkshops 2008. LNCS, vol. 4974. Springer, Heidelberg (2008)

    Google Scholar 

  20. Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., Machado, P. (eds.): EvoWorkshops 2009. LNCS, vol. 5484. Springer, Heidelberg (2009)

    Google Scholar 

  21. Greenfield, G.: Evolved ricochet compositions. In: Giacobini et al. [20], pp. 518–527

    Google Scholar 

  22. Hervàs, R., Robinson, J., Gervàs, P.: Evolutionary assistance in alliteration and allelic drivel. In: Giacobini et al. [18], pp. 537–546

    Google Scholar 

  23. Johnson, C.G.: Search and notions of creativity. In: Veale, T., Pease, A., Wiggins, G. (eds.) Proceedings of the IJCAI 2005 Workshop on Computational Creativity (2005)

    Google Scholar 

  24. Kötter, T., Berthold, M.R.: (missing) concept discovery in heterogeneous information networks. In: Proceedings of the Second International Conference on Computational Creativity. pp. 135–140 (2011), http://www.inf.uni-konstanz.de/bioml2/publications/Papers2011/KoBe11.pdf

  25. Krzeczkowska, A., El-Hage, J., Colton, S., Clark, S.: Automated collage generation—with intent. In: Ventura, D., et al. (eds.) Proceedings of the International Conference on Computational Creativity, pp. 36–40 (2010), http://creative-systems.dei.uc.pt/icccx

  26. Machado, P., Nunes, H., Romero, J.: Graph-based evolution of visual languages. In: Di Chio et al. [14], pp. 271–280

    Google Scholar 

  27. Machado, P., Romero, J., Santos, M., Cardoso, A., Manaris, B.: Adaptive critics for evolutionary artists. In: Raidl et al. [35], pp. 437–446

    Google Scholar 

  28. Magnus, C.: Evolutionary musique concrète. In: Rothlauf et al. [40], pp. 688–695

    Google Scholar 

  29. Manaris, B., Vaughan, D., Wagner, C., Romero, J., Davis, R.: Evolutionary music and the Zipf-Mandelbrot law: Developing fitness functions for pleasant music. In: Cagnoni et al. [6], pp. 65–72

    Google Scholar 

  30. McCormack, J.: Open problems in evolutionary music and art. In: Rothlauf et al. [39], pp. 428–436

    Google Scholar 

  31. McCormack, J., Bown, O.: Life’s what you make: Niche construction and evolutionary art. In: Giacobini et al. [20], pp. 528–537

    Google Scholar 

  32. Nagel, U., Thiel, K., Kötter, T., Piątek, D., Berthold, M.R.: Bisociative Discovery of Interesting Relations between Domains. In: Gama, J., Bradley, E., Hollmén, J. (eds.) IDA 2011. LNCS, vol. 7014, pp. 306–317. Springer, Heidelberg (2011), http://www.inf.uni-konstanz.de/bioml2/publications/Papers2011/NTKP+11.pdf

    Chapter  Google Scholar 

  33. Nemirovsky, P., Watson, R.: Genetic improvisation model a framework for real-time performance environments. In: Cagnoni et al. [6], pp. 547–558

    Google Scholar 

  34. Phon-Amnuaisuk, S., Law, E., Kuan, H.: Evolving music generation with som-fitness genetic programming. In: Giacobini et al. [18], pp. 557–566

    Google Scholar 

  35. Raidl, G.R., Cagnoni, S., Branke, J., Corne, D.W., Drechsler, R., Jin, Y., Johnson, C.G., Machado, P., Marchiori, E., Rothlauf, F., Smith, G.D., Squillero, G. (eds.): EvoWorkshops 2004. LNCS, vol. 3005. Springer, Heidelberg (2004)

    Google Scholar 

  36. Reddin, J., McDermott, J., ONeill, M.: Elevated pitch: Automated grammatical evolution of short compositions. In: Giacobini et al. [20], pp. 579–584

    Google Scholar 

  37. Romero, J., Machado, P., Santos, A.: On the socialization of evolutionary art. In: Giacobini et al. [20], pp. 557–566

    Google Scholar 

  38. Romero, J., Machado, P., Santos, A., Cardoso, A.: On the development of critics in evolutionary computation artists. In: Cagnoni et al. [6], pp. 559–569

    Google Scholar 

  39. Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G. (eds.): EvoWorkshops 2005. LNCS, vol. 3449. Springer, Heidelberg (2005)

    Google Scholar 

  40. Rothlauf, F., Branke, J., Cagnoni, S., Costa, E., Cotta, C., Drechsler, R., Lutton, E., Machado, P., Moore, J.H., Romero, J., Smith, G.D., Squillero, G., Takagi, H. (eds.): EvoWorkshops 2006. LNCS, vol. 3907. Springer, Heidelberg (2006)

    Google Scholar 

  41. Tufte, G., Gangvik, E.: Trans<–>former #13: Exploration and adaptation of evolution expressed in a dynamic sculpture. In: Giacobini et al. [19], pp. 509–514

    Google Scholar 

  42. Webb Young, J.: A Technique for Producing Ideas (original edition 1943). McGraw-Hill (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Johnson, C.G. (2012). Fitness in Evolutionary Art and Music: What Has Been Used and What Could Be Used?. In: Machado, P., Romero, J., Carballal, A. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2012. Lecture Notes in Computer Science, vol 7247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29142-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29142-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29141-8

  • Online ISBN: 978-3-642-29142-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics