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Learning representations for creative design using evolution

Published online by Cambridge University Press:  27 February 2009

Thorsten Schnier
Affiliation:
Key Centre of Design Computing, Department of Architectural and Design Science, University of Sydney NSW 2006, Australia
John S. Gero
Affiliation:
Key Centre of Design Computing, Department of Architectural and Design Science, University of Sydney NSW 2006, Australia

Extract

Creative design has been characterized in computational terms as “that design activity which occurs when a new variable is introduced into the design” (Gero, 1994). This is opposed to “routine design,” where “knowledge about variables, objectives expressed in terms of those variables, constraints expressed in terms of those variables, and the processes needed to find values for those variables, are all known a priori.” A third alternative, “innovative design,” occurs when no new variables are introduced, but when one or more variables are used with values outside the usual scope. In computational terms, routine design can also be seen as “search,” (sometimes also called “exploitation”) in so far as a certain, predefined search space is searched for a design solution. For creative design, where the search proceeds outside the boundaries of a predefined search space, the term “exploration” can be used.

Type
Research Abstracts
Copyright
Copyright © Cambridge University Press 1996

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References

REFERENCES

Gero, J.S. (1994). Computational models of creative design processes, In AI and Creativity (Dartnall, T., Ed.), pp. 269281. Kluwer, Dordrecht, The Netherlands.Google Scholar
Gero, J.S., & Schnier, T. (1995). Evolving representations of design cases and their use in creative design. In Preprints Computational Models of Creative Design (Gero, J.S., Maher, M.L. & Sudweeks, F., Eds.), pp. 343368. Key Centre of Design Computing, University of Sidney, Australia.Google Scholar