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Inverse Mapping with Sensitivity Analysis for Partial Selection in Interactive Evolution

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7834)

Abstract

Evolutionary algorithms have shown themselves to be useful interactive design tools. However, current algorithms only receive feedback about candidate fitness at the whole-candidate level. In this paper we describe a model-free method, using sensitivity analysis, which allows designers to provide fitness feedback to the system at the component level. Any part of a candidate can be marked by the designer as interesting (i.e. having high fitness). This has the potential to improve the design experience in two ways: (1) The finer-grain guidance provided by partial selections facilitates more precise iteration on design ideas so the designer can maximize her energy and attention. (2) When steering the evolutionary system with more detailed feedback, the designer may discover greater feelings of satisfaction with and ownership over the final designs.

Keywords

  • interactive evolution
  • sensitivity analysis
  • inverse mapping

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References

  1. Avila, S., Lisboa, A., Krahenbuhl, L., Carpes, W., Vasconcelos, J., Saldanha, R., Takahashi, R.: Sensitivity analysis applied to decision making in multiobjective evolutionary optimization 42, 1103–1106 (2006)

    Google Scholar 

  2. Caldwell, C., Johnston, V.S.: Tracking a criminal suspect through face-space with a genetic algorithm. In: ICGA 1991, pp. 416–421 (1991)

    Google Scholar 

  3. Dawkins, R.: The blind watchmaker: why the evidence of evolution reveals a universe without design. Norton (1986)

    Google Scholar 

  4. Eisenmann, J., Lewis, M., Cline, B.: Interactive Evolution for Designing Motion Variants. In: Madani, K., Correia, A.D., Rosa, A., Filipe, J. (eds.) Computational Intelligence. SCI, vol. 343, pp. 135–149. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  5. Erhan, H., Woodbury, R., Salmasi, N.H.: Visual sensitivity analysis of parametric design models: improving agility in design. Master’s thesis, School of Interactive Arts and Technology - Simon Fraser University (2009)

    Google Scholar 

  6. Ester, M., Kriegel, H., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proc. of the 2nd Int’l Conf. on Knowledge Discovery and Data Mining, pp. 226–231 (1996)

    Google Scholar 

  7. Hancock, P., Frowd, C.: Evolutionary generation of faces. In: Proc. of AISB (1999)

    Google Scholar 

  8. Kim, V.G., Li, W., Mitra, N.J., DiVerdi, S., Funkhouser, T.: Exploring collections of 3D models using fuzzy correspondences. ACM Trans. Graph. 31(4) (July 2012)

    Google Scholar 

  9. Lee, J.H., Kim, H.S., Cho, S.B.: Accelerating evolution by direct manipulation for interactive fashion design. In: Proc. Fourth Int’l. Conf. on Comp. Intelligence and Multimedia Applications, ICCIMA 2001, pp. 343–347. IEEE (2001)

    Google Scholar 

  10. Lewis, M.: Aesthetic evolutionary design with data flow networks. In: Soddu, C. (ed.) Proc. of Generative Arts (2000)

    Google Scholar 

  11. Lewis, M.: Evolutionary visual art and design. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 3–37. Springer, Heidelberg (2007)

    Google Scholar 

  12. Li, Y., Hu, C., Chen, M., Hu, J.: Investigating Aesthetic Features to Model Human Preference in Evolutionary Art. In: Machado, P., Romero, J., Carballal, A. (eds.) EvoMUSART 2012. LNCS, vol. 7247, pp. 153–164. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  13. Lim, I.S.: Evolving facial expressions. In: IEEE Int’l. Conf. on Evol. Comput., vol. 2, pp. 515–520. IEEE (November 1995)

    Google Scholar 

  14. Morris, M.D.: Factorial sampling plans for preliminary comp. experiments. Technometrics 33(2), 161–174 (1991)

    CrossRef  Google Scholar 

  15. Parmee, I.C., Cvetković, D.C., Watson, A.H., Bonham, C.R.: Multiobjective satisfaction within an interactive evol. design environment. Evol. Comput. 8(2), 197–222 (2000)

    CrossRef  Google Scholar 

  16. Romero, J., Machado, P., Carballal, A., Osorio, O.: Aesthetic Classification and Sorting Based on Image Compression. In: 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, pp. 394–403. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  17. Saltelli, A.: Global sensitivity analysis: the primer. John Wiley (2008)

    Google Scholar 

  18. Semet, Y.: Interactive evolutionary computation: a survey of existing theory. University of Illinois (2002)

    Google Scholar 

  19. Sims, K.: Artificial evolution for computer graphics. In: Proc. SIGGRAPH 1991, vol. 25, pp. 319–328. ACM, New York (1991)

    Google Scholar 

  20. Takagi, H., Kishi, K.: On-line knowledge embedding for an interactive EC-based montage system. In: Third Int’l. Conf. Knowledge-Based Intelligent Information Engineering Systems, pp. 280–283 (December1999)

    Google Scholar 

  21. Takagi, H.: New IEC Research and Frameworks. In: Fodor, J., Kacprzyk, J. (eds.) Aspects of Soft Computing, Intelligent Robotics and Control. SCI, vol. 241, pp. 65–76. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

  22. Todd, S., Latham, W.: Evolutionary art and computers. Academic Press (1992)

    Google Scholar 

  23. Umetani, N., Igarashi, T., Mitra, N.J.: Guided exploration of physically valid shapes for furniture design. ACM Trans. Graph (Proc. of SIGGRAPH 2012) 31(4) (2012)

    Google Scholar 

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Eisenmann, J., Lewis, M., Parent, R. (2013). Inverse Mapping with Sensitivity Analysis for Partial Selection in Interactive Evolution. In: Machado, P., McDermott, J., Carballal, A. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2013. Lecture Notes in Computer Science, vol 7834. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36955-1_7

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  • DOI: https://doi.org/10.1007/978-3-642-36955-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

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