AI & Architecture

Our work proposes to evidence this promise when applied to the built environment. Specifically, we offer to apply AI to floor plans analysis and generation. Our methodology follows two main intuitions (1) the creation of building plans is a non-trivial technical challenge, although encompassing standard optimization technics, and (2) the design of space is a sequential process, requiring successive design steps across different scales (urban scale, building scale, unit scale). Then, in order to harness these two realities, we have chosen nested Generative Adversarial Neural Networks or GANs. Such models enable us to capture more complexity across encountered floor plans and to break down the complexity by tackling problems through successive steps.