CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures
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In this work, we present progress on the application of contemporary ML techniques to the design process in the architecture, engineering, and construction (AEC) industry. We introduce a technique to partially circumvent the data hungriness of neural networks, which is a significant impediment to their application outside of the ML research community. We also show results on the applicability of this technique to real-world drawings and present research that addresses how some fundamental attributes of drawings as images affect the way they are interpreted in deep neural networks. Our primary contribution is a technique to train a neural network to segment real-world architectural drawings after using only generated pseudodrawings.
In the paper, we describe the algorithms of the computational evaluation method. We also show how it can be used to introduce fabrication considerations into the design process by using it to rationalize several types of panels. Additionally, we demonstrate how the method can be used in complex, large-scale architectural projects to save machining time and materials by evaluating and altering the paneling subdivision.
We argue a way of creating intelligent architecture, not through classical Artificial Intelligence (AI), but rather through Artificial Life (ALife), embracing the aesthetic emergent possibilities that can spontaneously arise from this approach. In order to make these ideas of emergent life more tangible we present this paper in four integrated parts, namely: narrative, material, hardware and computation. The Edge of Chaos installation is an explicit realization of creating emergent systems and translating them into an architectural design. Our results demonstrate the effectiveness of a custom CA for maximizing aesthetic impact while minimizing the live time of architectural kinetic elements.
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