Skip to main content

A Local Search Interface for Interactive Evolutionary Architectural Design

  • Conference paper

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

Abstract

A designer should be able to express their intentions with a design tool. This paper describes an evolutionary design tool that enables the architect to directly interact with the encoding of designs they find aesthetically pleasing. Broadening interaction beyond simple evaluation increases the amount of feedback and bias a user can apply to the search. Increased feedback will have the effect of directing the algorithm to more fruitful areas of the search space. We conduct user trials on an interface for making localised changes to an individual and evaluate if it is capable of directing search. Examination of the locality of changes made by the users provides an insight into how they explore the search space.

Keywords

  • Search Space
  • Derivation Tree
  • Structural Mutation
  • User Selection
  • Nodal Mutation

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: 10.1007/978-3-642-29142-5_3
  • Chapter length: 12 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   54.99
Price excludes VAT (USA)
  • ISBN: 978-3-642-29142-5
  • 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   69.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bush, B., Sayama, H.: Hyperinteractive evolutionary computation. IEEE Transactions on Evolutionary Computation 15(3), 1–10 (2011)

    CrossRef  Google Scholar 

  2. Byrne, J., O’Neill, M., Brabazon, A.: Structural and nodal mutation in grammatical evolution. In: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, pp. 1881–1882. ACM (2009)

    Google Scholar 

  3. Byrne, J., Hemberg, E., O’Neill, M.: Interactive operators for evolutionary architectural design. In: GECCO 2011: Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation, July 12-16, pp. 43–44. ACM, Dublin (2011)

    Google Scholar 

  4. Byrne, J., McDermott, J., López, E.G., O’Neill, M.: Implementing an intuitive mutation operator for interactive evolutionary 3d design. In: IEEE Congress on Evolutionary Computation, pp. 1–7. IEEE (2010)

    Google Scholar 

  5. Byrne, J., O’Neill, M., McDermott, J., Brabazon, A.: An Analysis of the Behaviour of Mutation in Grammatical Evolution. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds.) EuroGP 2010. LNCS, vol. 6021, pp. 14–25. Springer, Heidelberg (2010)

    CrossRef  Google Scholar 

  6. Cook, S.A.: The complexity of theorem-proving procedures. In: Proceedings of the Third Annual ACM Symposium on Theory of Computing, STOC 1971, pp. 151–158. ACM, New York (1971), http://doi.acm.org/10.1145/800157.805047

    CrossRef  Google Scholar 

  7. Dempsey, I., O’Neill, M., Brabazon, A.: Foundations in Grammatical Evolution for Dynamic Environments. Springer (2009)

    Google Scholar 

  8. Efron, B., Tibshirani, R.: An introduction to the bootstrap. In: Monographs on Statistics and Applied Probability. Chapman & Hall (1993), http://books.google.ie/books?id=gLlpIUxRntoC

  9. Hagberg, A.A., Schult, D.A., Swart, P.J.: Exploring network structure, dynamics, and function using networkx. In: Proceedings of the 7th Python in Science Conference, Pasadena, CA USA, pp. 11–15 (2008)

    Google Scholar 

  10. Hayashida, N., Takagi, H.: Visualized IEC: Interactive evolutionary computation with multidimensional data visualization. IECON-PROCEEDINGS 4, 2738–2743 (2000)

    Google Scholar 

  11. Hayashida, N., Takagi, H.: Acceleration of EC convergence with landscape visualization and human intervention. Applied Soft Computing 1, 245–256 (2002)

    CrossRef  Google Scholar 

  12. Hornby, G.: Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp. 1729–1736. ACM (2005)

    Google Scholar 

  13. iecgallery: Online image gallery (2011), http://imgur.com/a/24fP9

  14. Kosorukoff, A.: Human based genetic algorithm. In: 2001 IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, pp. 3464–3469. IEEE (2001)

    Google Scholar 

  15. McDermott, J., Byrne, J., Swafford, J.M., O’Neill, M., Brabazon, A.: Higher-order functions in aesthetic EC encodings. In: 2010 IEEE World Congress on Computational Intelligence, pp. 2816–2823. IEEE Press, Barcelona (2010)

    Google Scholar 

  16. O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Kluwer Academic Publishers (2003)

    Google Scholar 

  17. O’Reilly, U.M., Hemberg, M.: Integrating generative growth and evolutionary computation for form exploration. Genetic Programming and Evolvable Machines 8(2), 163–186 (2007); special issue on developmental systems

    CrossRef  Google Scholar 

  18. Rothlauf, F.: Representations for Genetic and Evolutionary Algorithms, 2nd edn. Physica-Verlag (2006)

    Google Scholar 

  19. Shea, K., Aish, R., Gourtovaia, M.: Towards integrated performance-driven generative design tools. Automation in Construction 14(2), 253–264 (2005)

    CrossRef  Google Scholar 

  20. Software, R.: Grasshopper, generative modeling (2010), http://www.grasshopper3d.com/

  21. Sytems, B.: Generative components, v8i (2011), http://www.bentley.com/getgc/

  22. Takagi, H., Kishi, K.: On-line knowledge embedding for an interactive ec-based montage system. In: Third International Conference on Knowledge-Based Intelligent Information Engineering Systems, pp. 280–283. IEEE (1999)

    Google Scholar 

  23. Takagi, H.: Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation. Proc. of the IEEE 89(9), 1275–1296 (2001)

    CrossRef  Google Scholar 

  24. Weber, E.: De Pulsu, resorptione, auditu et tactu: Annotationes anatomicae et physiologicae. CF Koehler (1834)

    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

Byrne, J., Hemberg, E., Brabazon, A., O’Neill, M. (2012). A Local Search Interface for Interactive Evolutionary Architectural Design. 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_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29142-5_3

  • 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)