Advertisement

Notes for an Improvisational Specification of Design Spaces

  • Alexandros CharidisEmail author
Conference paper

Abstract

Classical specifications for design spaces are characterized by an implicit need for a priori closure of descriptions of alternative designs before calculating. In this paper, an improvisational specification for design spaces made of shapes is presented. Shapes created visually and without prior description are recorded in a computation history. This history is read backwards to specify descriptions of recorded shapes and the space in which they are closed members. Descriptions of shapes, and the space in which they lie, are both made on the go as rules are applied in the course of a computation; every new visual action (rule application) redescribes the space in which the shapes obtained “thus far” belong. A reconsideration of the classical notion of a design space and its various uses in design theory is suggested, emphasizing a need to reconcile traditional formalistic pursuits that aim at “capturing” descriptions of alternative design possibilities with the open-ended, improvisational nature of creative work in architecture, the visual arts, and related areas of spatial design.

References

  1. 1.
    Krstic D (2016) From shape computations to shape decompositions. In: Gero JS (ed) Design computing and cognition ’16, Springer, Netherlands, pp 361–376Google Scholar
  2. 2.
    Stiny G (1994) Shape rules: closure, continuity, and emergence. Environ Plan 20:359–362CrossRefGoogle Scholar
  3. 3.
    Stiny G (2006) Shape: talking about seeing and doing. The MIT Press, CambridgeCrossRefGoogle Scholar
  4. 4.
    Nilsson NJ (1982) Principles of artificial intelligence. Springer, BerlinCrossRefGoogle Scholar
  5. 5.
    Charidis A (2018) Improvisational specification of design spaces. Master’s thesis, Departments of Architecture and Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyGoogle Scholar
  6. 6.
    McKinsey JCC, Tarski A (1944) The algebra of topology. Ann Math 45:141–191MathSciNetCrossRefGoogle Scholar
  7. 7.
    Cagan J, Campbell MI, Finger S, Tomiyama T (2005) A framework for computational design synthesis: model and applications. J Comput Inf Sci Eng 5:171–181CrossRefGoogle Scholar
  8. 8.
    Fensel D (2000) Problem solving methods: understanding, description, development and reuse. In: Lecture notes in artificial intelligence 1971. Springer, BerlinGoogle Scholar
  9. 9.
    Radford D, Gero J (1998) Design by optimization in architecture, building, and construction. Wiley, USAGoogle Scholar
  10. 10.
    Woodburry RF (1991) Searching for designs: paradigm and practice. Build Environ 26:61–73CrossRefGoogle Scholar
  11. 11.
    Gero JS (1993) Towards a model of exploration in computer-aided design. In: Gero JS, Tyugu N (ed) Formal methods for computer-aided design, North-Holland, pp 315–336Google Scholar
  12. 12.
    Stouffs R (eds) (2006) Design spaces: the explicit representation of spaces of alternatives. Artif Intell Eng Des Anal Manuf Special Issue 20(2)Google Scholar
  13. 13.
    Ligeza A (2006) Logical foundations for rule-based systems, 2nd edn. In: Studies in computational intelligence, vol 11. Springer, BerlinGoogle Scholar
  14. 14.
    Knight T (2015) Shapes and other things. Nexus Netw J 17:963–980CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Massachusetts Institute of TechnologyCambridgeUSA

Personalised recommendations