Relevant floor plans can be generated before planning the layout of furniture pieces. Recently, Merrell et al. [2010] proposed a data- driven method to generate residential building layouts. In their work, 120 examples of architectural programs are used to train a Bayesian network that captures the relationships among different rooms. Given certain user requirements as priors, the Bayesian net- work can then be used to generate a floor plan, which is iteratively modified to incorporate desirable human factors. The result is a synthesized floor plan for a residential building. We also note the work of Chun and Lai [1997], which encapsu- lates architectural design knowledge into an expert system. The system.
