A master thesis from Aalborg University
Speculative Hybrids: Investigating the generation of conceptual architectural forms through the use of Machine Learning.
[Speculative Hybrids]
Author(s)
Term
4. term
Education
Publication year
2022
Submitted on
2022-06-03
Pages
88 pages
Abstract
Design Thinking aims at solving problems that have no definite formulation, no explicit basis for terminating the problem-solving activity, and where differing outcomes may occur from differing problem formulations. Most of the design processes have already come under the spell of the digital age. In order to explore the realm and capabilities of contemporary architectural design, an analysis of its enhancement through digital tools and the suggestion of a method for problem-space exploration will be demonstrated. In Speculative Hybrids we employ machine learning algorithms in order to generate conceptual architectural forms with respect to site-specific regulations. More specifically, Generative Adversarial Networks are implemented to generate annotated point clouds. The iterative power of such a tool facilitates the design process by suggesting a plausible array of satisfactory outcomes in space-problem structuring, and can assist in the formulation of more efficient problem-solving processes.
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