Abstract
The Chinese garden style is not only a decorative aesthetic but also a composition of spaces. Chinese gardening is about creating narrative spatial sequences, and the composition of the views in each space is also important. We propose to simulate these approaches with AI. Firstly, we used the pix2pix algorithm to generate a plan layout and determine the paths that connect the spatial sequences. secondly, we will enter the first-person view. Whereas traditional architects design by plans and axonometric drawings, our work focuses on the ‘spirit of place’. We used Isovist to simulate the spatial elements that one sees as he or she moves through space over time and encoded these spatial elements, then we chose RNN (LSTM) to learn this spatial sequence composition of the ‘spirit of place’, and to generate a practical project with the ‘spirit of place’ in Chinese gardens. The RNN (LSTM) model can handle the information of the sequence well, that is, the input before and the input after are related, and in a spatial sequence, the spatial nodes before and the spatial nodes after will also jointly form a sense of spatial rhythm. Finally we tried to materialize the model with CycleGAN to refine the workflow of the auxiliary architectural design. We tested this methodology in a renovation program for a Chinese village to observe the ‘spirit of place’ created by AI(Artificial Intelligence). This approach could potentially be applied to other user experience-oriented aided designs. Our objective is to establish a workflow that enables architects to collaborate better with AI.
Z. Wang and X. Zhang—These authors contributed equally to this work.
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Wang, Z., Zhang, X. (2023). AI-Assisted Exploration of the Spirit of Place in Chinese Gardens from the Perspective of Spatial Sequences. In: Turrin, M., Andriotis, C., Rafiee, A. (eds) Computer-Aided Architectural Design. INTERCONNECTIONS: Co-computing Beyond Boundaries. CAAD Futures 2023. Communications in Computer and Information Science, vol 1819. Springer, Cham. https://doi.org/10.1007/978-3-031-37189-9_19
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