  This study integrates artificial intelligence and computational design tools
to extract information from architectural heritage. Photogrammetry-based point
cloud models of brick walls from the Anatolian Seljuk period are analysed in
terms of the interrelated units of construction, simultaneously considering
both the inherent symmetries and irregularities. The real-world data is used as
input for acquiring the stochastic parameters of spatial relations and a set of
parametric shape rules to recreate designs of existing and hypothetical brick
walls within the style. The motivation is to be able to generate large data
sets for machine learning of the style and to devise procedures for robotic
production of such designs with repetitive units.
