Semantic-driven Graph Transformations in Floor Plan Design

This paper deals with supporting the design of building floor plans. Floor layouts are represented by labelled and attributed graphs. These graphs are generated using graph grammars, i.e., systems for transforming graphs according to specified rules. The key feature of a graph grammar is that graph representations are obtained by successively adding nodes and edges by applying the rules during the generation process with the use of the so-called embedding principle. The existing embedding principles are often not sufficient to create solutions which fulfill the design criteria. The main contribution of this paper is a generative graph grammar with an innovative semantic-driven embedding where graph attribute values are taken into account while creating new edges. The proposed approach enables automatic generation of graphs corresponding to new layout designs with geometrical properties specified by graph attributes. It is illustrated by examples of apartment floor layouts generated by a prototype application implemented in Python.