Generative design (GD) algorithms is a fast growing field. From the point of view of Design Science, this fast growth leads to wonder what exactly is 'generated' by GD algorithms and how? In the last decades, advances in design theory enabled to establish conditions and operators that characterize design generativity. Thus, it is now possible to study GD algorithms with the lenses of Design Science in order to reach a deeper and unified understanding of their generative techniques, their differences and, if possible, find new paths for improving their generativity. In this paper, first, we rely on C-K ttheory to build a canonical model of GD, based independent of the field of application of the algorithm. This model shows that GD is generative if and only if it builds, not one single artefact, but a "topology of artefacts" that allows for design constructability, covering strategies, and functional comparability of designs. Second, we use the canonical model to compare four well documented and most advanced types of GD algorithms. From these cases, it appears that generating a topology enables the analyses of interdependences and the design of resilience.
CITATION STYLE
Hatchuel, A., Le Masson, P., Thomas, M., & Weil, B. (2021). What is generative in generative design tools? Uncovering topological generativity with a C-K model of evolutionary algorithms. In Proceedings of the Design Society (Vol. 1, pp. 3419–3429). Cambridge University Press. https://doi.org/10.1017/pds.2021.603
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