Skip to main content

Genr8: Architects’ Experience with an Emergent Design Tool

  • Chapter

Part of the Natural Computing Series book series (NCS)

Summary

We present the computational design tool Genr8 and six different architectural projects making extensive use of Genr8. Genr8 is based on ideas from Evolutionary Computation (EC) and Artificial Life and it produces surfaces using an organic growth algorithm inspired by how plants grow. These algorithms have been implemented as an architect’s design tool and the chapter provides an illustration of the possibilities that the tool provides.

Keywords

  • Evolutionary Algorithm
  • Evolutionary Computation
  • Design Tool
  • Grammatical Evolution
  • Growth Algorithm

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.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-540-72877-1_8
  • Chapter length: 22 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)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tsui, E. (1999). Evolutionary Architecture: Nature as a Basis for Design. John Wiley

    Google Scholar 

  2. Thompson, D. (1961). On Growth and Form. Cambridge University Press

    Google Scholar 

  3. Frazer, J. (1995). An Evolutionary Architecture. Architectural Association. London

    Google Scholar 

  4. von Neumann, J. (1966). The Theory of Self-Reproducing Automata. University of Illinois Press

    Google Scholar 

  5. Broughton, T., Coates, P., Jackson, H. (1999). Exploring 3d design worlds using Lindenmayer systems and genetic programming. In Bentley, P.J., ed.: Evolutionary Design by Computers. Morgan Kaufmann

    Google Scholar 

  6. Hornby, G.S., Pollack, J.B. (2001). The advantages of generative grammatical encodings for physical design. In: Congress on Evolutionary Computation

    Google Scholar 

  7. Kumar, S., Bentley, P.J., eds. (2003). On Growth, Form and Computers. Elsevier

    Google Scholar 

  8. Murawski, K., Arciszewski, T., Jong, K.A.D. (2000). Evolutionary computation in structural design. Eng. Comput. (Lond.), 16(3-4): 275–286

    MATH  Google Scholar 

  9. Shi, X.G., Gero, J.S. (2000). Design families and design individuals. Eng. Comput. (Lond.), 16(3-4): 253–263

    MATH  Google Scholar 

  10. Maher, M.L. (2000). A model of co-evolutionary design. Eng. Comput. (Lond.), 16(3-4): 195–208

    MATH  Google Scholar 

  11. Gero, J.S., Kazakov, V. (2000). Adaptive enlargement of state spaces in evolutionary designing. AI EDAM, 14(1): 31–38

    CrossRef  Google Scholar 

  12. Gero, J.S., Kazakov, V. (2001). A genetic engineering approach to genetic algorithms. Evolutionary Computation, 9(1): 71–92

    CrossRef  Google Scholar 

  13. Bentley, P.J., ed. (1999). Evolutionary Design by Computers. Morgan Kaufmann

    Google Scholar 

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

    Google Scholar 

  15. O’Reilly, U.M., Hemberg, M. (2007). Integrating generative growth and evolutionary computation for form exploration. Genetic Programming and Evolvable Machines, 8(2): 163–186

    CrossRef  Google Scholar 

  16. Prusinkiewicz, P., Lindenmayer, A. (1991). The Algorithmic Beauty of Plants. Springer

    Google Scholar 

  17. O’Neill, M., Ryan, C. (2003). Grammatical Evolution – Evolving Programs in an Arbitrary Language. Kluwer Academic Publishers

    Google Scholar 

  18. Mitchell, M. (1996). An Introduction to Genetic Algorithms. MIT Press

    Google Scholar 

  19. Koza, J.R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press

    Google Scholar 

  20. Romero, J., Machado, P., Santos, A., Cardoso, A. (2003). On the development of critics in evolutionary computation artists. In 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.: Applications of Evolutionary Computing, EvoWorkshops2003: EvoBIO, EvoCOP, EvoIASP, EvoMUSART, EvoROB, EvoSTIM. Vol. 2611 of LNCS. University of Essex, England, UK. Springer-Verlag, 562–573

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Hemberg, M., O’Reilly, UM., Menges, A., Jonas, K., Gonçalves, M.d.C., Fuchs, S.R. (2008). Genr8: Architects’ Experience with an Emergent Design Tool. 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_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72877-1_8

  • 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)