Furniture layout design aided system using subjective reward

Several studies for layout design optimization depend on evaluation indices with necessary passage, spaciousness, etc. It is difficult to obtain a friendly layout by using conventional methods. The layout design-aided model in this study is a residence space, and there are eight types of furniture. All furniture is first allocated to each room by using a genetic algorithm. All allocated furniture's initial arrangements in each room are then determined by using Q-learning. A user checks the initial layout through virtual reality and evaluates it subjectively. The layout for a specific user is flexibly fixed by applying Q-learning, and a user subjective reward is added. As a result of observer experiments, more than half of the furniture can be arranged in an ideal position for a user, and a satisfactory layout is successfully generated.