Expertise, playfulness and analogical reasoning: three strategies to train Artificial Intelligence for design applications

Autor: Gabriele Mirra, Alberto Pugnale
Rok vydání: 2022
Zdroj: Architecture, Structures and Construction. 2:111-127
ISSN: 2730-9894
2730-9886
Popis: This paper presents a theoretical framework for the implementation of Artificial Intelligence (AI) in architectural and structural design processes, and it is complemented by some practical applications. The aim is to demonstrate that AI can be used to simulate certain aspects of human cognition and can therefore be integrated into CAD software to support conceptual design and idea generation in a number of different ways. The aim of this study is also to investigate to what extent AI models can interact with a designer to explore future forms of human–machine interaction, including autonomous and participative design. This study identifies and applies AI models to simulate three distinct learning mechanisms: design expertise, playfulness and analogical reasoning. Each strategy has been applied to train different AI models, including generative models and reinforcement learning agents. In the first application, the AI model extracts visual features from a dataset of shell and spatial structures, and then recombines such features to generate new design propositions. In the second application, an AI agent learns a design strategy to solve a toy-design problem with no prior knowledge of precedents. The third application illustrates that AI can be trained to discover meaningful features from biological forms and generate simple design objects through the visual abstraction of such forms. The applications demonstrate the ability of AI to synthesise design options and interact with a designer through visual data formats, such as 2D images and 3D models. This work does not focus on assessing the usefulness of AI models in a real-world design scenario, or on comparing AI with current computational design tools and approaches. It instead investigates different forms of design exploration for computational design purposes, thus paving the way for the development of future autonomous and participative design systems.
Databáze: OpenAIRE
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