Skip to main content
Book cover

The Art of Artificial Evolution pp 227–247Cite as

Artificial Art Made by Artificial Ants

  • Chapter

Part of the Natural Computing Series book series (NCS)

Summary

We present how we have considered the artificial ant paradigm as a tool for the generation of music and painting. From an aesthetic perspective, we are interested in demonstrating that swarm intelligence and self-organization can lead to spatio-temporal structures that can reach an artistic dimension. In our case, the use of artificial pheromones can lead to the creation of melodies thanks to a cooperative behavior of the ant-agents but also to the emergence of abstract paintings thanks to competitive behaviors within the artificial colonies. The user’s point of view is also taken into account through interactive genetic algorithms.

Keywords

  • Travel Salesman Problem
  • Collective Behavior
  • Swarm Intelligence
  • Music Composition
  • Computer Music

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.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-540-72877-1_11
  • Chapter length: 21 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   149.00
Price excludes VAT (USA)
  • ISBN: 978-3-540-72877-1
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   189.00
Price excludes VAT (USA)
Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bonabeau, E., Dorigo, M., Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press. New York

    MATH  Google Scholar 

  2. Root-Bernstein, R. (2001). Music, creativity and scientific thinking. Leonardo, 34(1): 63–68

    CrossRef  Google Scholar 

  3. Guéret, C., Monmarché, N., Slimane, M. (2004). Ants can play music. In: Fourth International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS 2004). Lecture Notes in Computer Science. Université Libre de Bruxelles, Belgique. Springer, 310–317

    Google Scholar 

  4. Aupetit, S., Bordeau, V., Monmarché, N., Slimane, M., Venturini, G. (2003). Interactive Evolution of Ant Paintings. In: IEEE Congress on Evolutionary Computation. Vol. 2. Canberra. IEEE Press, 1376–1383

    Google Scholar 

  5. Hölldobler, B., Wilson, E. (1990). The Ants. Springer

    Google Scholar 

  6. Stützle, T., Dorigo, M. (1999). ACO algorithms for the Traveling Salesman Problem. In Miettinen, K., Mäkelä, M., Neittaanmäki, P., Periaux, J., eds.: Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications. John Wiley & Sons

    Google Scholar 

  7. Dorigo, M., Stützle, T. (2004). Ant Colony Optimization. MIT Press

    Google Scholar 

  8. Lopez de Mantaras, R., Arcos, J. (2002). AI and music, from composition to expressive performance. AI magazine, 23(3): 43–57

    Google Scholar 

  9. T., J. (1996). Self-Similar Melodies. Edition 75

    Google Scholar 

  10. Chen, C., Miikkulainen, R. (2001). Creating melodies with evolving recurrent neural networks. In: Proceedings of the 2001 International Joint Conference on Neural Networks (IJCNN–2001), 2241–2246

    Google Scholar 

  11. Eck, D., Schmidhuber, J. (2002). Finding temporal structure in music: Blues improvisation with LSTM recurrent networks. In Bourlard, H., ed.: Proceedings of IEEE Workshop on Neural Networks for Signal Processing XII, 747–756

    Google Scholar 

  12. Henz, M., Lauer, S., Zimmermann, D. (1996). COMPOzE — intention-based music composition through constraint programming. In: Proceedings of the 8th IEEE International Conference on Tools with Artificial Intelligence. Toulouse, France. IEEE Computer Society Press, 118–121

    CrossRef  Google Scholar 

  13. Wulfhorst, R.D., Flores, L.V., Nakayama, L., Flores, C.D., Alvares, L.O.C., Viccari, R.M. (2001). An open architecture for a musical multi-agent system. In: Proceedings of Brazilian Symposium on Computer Music

    Google Scholar 

  14. Moroni, A., Manzolli, J., Von Zuben, F., Gudwin, R. (2000). Vox populi: An interactive evolutionary system for algorithmic music composition. Leonardo Music Journal, 10: 49–54

    CrossRef  Google Scholar 

  15. Todd, P., Werner, G. (1998). Frankensteinian Methods for Evolutionary Music Composition. In Griffith, N., Todd, P., eds.: Musical Networks: Parallel Distributed Perception and Performance. MIT Press/Bradford Books

    Google Scholar 

  16. Bentley, P., Corne, D., eds. (2001). Creative Evolutionary Systems. Morgan Kaufmann

    Google Scholar 

  17. Cope, D. (1990). Pattern matching as an engine for the computer simulation of musical style. In Association, I.C.M., ed.: Proceedings of the International Computer Music Conference. San Francisco, 288–291

    Google Scholar 

  18. Franklin, J. (2001). Multi-phase learning for jazz improvisation and interaction. In: Proceedings of the Eighth Biennal Symposium on Art and Technology. New London, Connecticut

    Google Scholar 

  19. Biles, J. (1994). GEMJAM: a genetic algorithm for generating jazz solos. In: Proceedings of the International Computer Music Conference. San Francisco. International Computer Music Association, 131–137

    Google Scholar 

  20. Morales-Manzanares, R., Morales, E., Danenberg, R., Berger, J. (2001). SICIB: An interactive music composition system using body movements. New Music Research, 25(2): 25–36

    Google Scholar 

  21. Todd, P., Miranda, E. (2003). Putting some (artificial) life into models of musical creativity. In Deliege, I., Wiggins, G., eds.: Musical Creativity: Current Research in Theory and Practise. Psychology Press

    Google Scholar 

  22. Blackwell, T., P., B. (2002). Improvised music with swarms. In: Proceedings of the World Congress on Evolutionary Computation (CEC’2002), 1462–1467

    Google Scholar 

  23. Blackwell, T., M., Y. (2004). Swarm granulator. In Raidl, G.R., et al., eds.: Applications of Evolutionary Computing, EvoWorkshops2004: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, EvoSTOC. Lecture Notes in Computer Science. Coimbra, Portugal. Springer, 399–408

    Google Scholar 

  24. Tzafestas, E. (2000). Integrating drawing tools with behavioral modeling in digital painting. In: Proceedings of the 1st International Workshop “Bridging the Gap: Bringing Together New Media Artists and Multimedia Technologists”. Los Angeles, CA

    Google Scholar 

  25. Moura, L., Garcia Pereira, H. (2004). Man + Robots: Symbiotic Art. Institut d’art contemporain. Villeurbanne, France

    Google Scholar 

  26. Urbano, P. (2005). Playing in the pheromone playground: Experiences in swarm painting. In Rothlauf, F., et al., eds.: Applications on Evolutionary Computing: EvoWorkkshops 2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, and EvoSTOC. Lecture Notes in Computer Science. Lausanne, Switzerland. Springer Berlin/Heidelberg, 527

    Google Scholar 

  27. Ramos, V., Almeida, F. (2000). Artificial ant colonies in digital image habitats – a mass behaviour effect study on pattern recognition. In Dorigo, M., Middendoff, M., Stützle, T., eds.: From Ant Colonies to Artificial Ants: Proceedings of the Second International Workshop on Ant Algorithms (ANTS’2000). Brussels, Belgium, 113–116

    Google Scholar 

  28. Bourjot, C., Chevrier, V., Thomas, V. (2003). A new swarm mechanism based on social spiders colonies: from web weaving to region detection. Web Intelligence and Agent Systems: An International Journal – WIAS

    Google Scholar 

  29. Campolongo, G., Vena, S. (2006). Science of networks and music: A new approach on musical analysis and creation. In Rothlauf, F., et al., eds.: Applications of Evolutionary Computing, EvoWorkshops2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoInteraction, EvoMUSART, EvoSTOC. Lecture Notes in Computer Science. Springer, 642–651

    Google Scholar 

  30. Dorigo, M., Maniezzo, V., Colorni, A. (1996). The Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics–Part B, 26(1): 29–41

    CrossRef  Google Scholar 

  31. Minsky, M. (1993). Music, Mind and Meaning. In Schwanauer, S., Levitt, D., eds.: Machine Models of Music. MIT Press, 327–354

    Google Scholar 

  32. Lebocey, P., Fortune, J., Puret, A., Monmarché, N., Gaucher, P., Slimane, M., Lastu, D. (2006). On the popularization of artificial insects: an interactive exhibition for a wide audience to explain and demonstrate computer science and robotic problem solving taking inspiration of insects. In Dorigo, M., Gambardella, L., Birattari, M., Martinoli, A., Poli, R., Stützle, T., eds.: Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006. Lecture Notes in Computer Science. Bruxelles, Belgium. Springer, 476–483

    Google Scholar 

  33. Monmarché, N., Slimane, M., Venturini, G. (2003). Fourmis artistiques ou l’art artificiel pictural et musical. In: Hypertextes et Hypermédias, Réalisations, Outils & Méthodes (H2PTM’03). Paris, France. Hermes, 109–118

    Google Scholar 

  34. Greenfield, G. (2005). Evolutionary methods for ant colony paintings. In Rothlauf, F., et al., eds.: Applications on Evolutionary Computing: EvoWorkkshops 2005: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoMUSART, and EvoSTOC. Lecture Notes in Computer Science. Lausanne, Switzerland, 478

    Google Scholar 

  35. Lesbros, V. (1996). From images to sounds, a dual representation. Computer Music Journal, 20(3): 59–69

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tours Laboratoire d’Informatique, Université François Rabelais, France

    Nicolas Monmarché, Isabelle Mahnich & Mohamed Slimane

Authors
  1. Nicolas Monmarché
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Isabelle Mahnich
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohamed Slimane
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Information and Communication Technologies, University of A Coruña Campus de Elvina, 15071 La Coruña, Spain

    Juan Romero

  2. CISUC Dept. of Informatics Engineering, University of Coimbra, 3030 Coimbra, Portugal

    Penousal Machado

Rights and permissions

Reprints and Permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Monmarché, N., Mahnich, I., Slimane, M. (2008). Artificial Art Made by Artificial Ants. In: Romero, J., Machado, P. (eds) The Art of Artificial Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72877-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72877-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72876-4

  • Online ISBN: 978-3-540-72877-1

  • eBook Packages: Computer ScienceComputer Science (R0)