Computing narratives of cognitive user experience for building design analysis KR for industry scale computer-aided architecture design

Abstract

We present a cognitive design assistance system equipped with analytical capabilities aimed at anticipating architectural building design performance with respect to people-centred functional design goals. The paper focuses on the system capability to generate narratives of visuo-locomotive user experience from digital computer-aided architecture design (CAAD) models. The system is based on an underlying declarative narrative representation and computation framework pertaining to conceptual, geometric, and qualitative spatial knowledge. The semantics of the declarative narrative model, i.e., the overall representation and computation model, is founded on: (a) conceptual knowledge formalised in an OWL ontology; (b) a general spatial representation and reasoning engine implemented in constraint logic programming; and (c) a declaratively encoded (narrative) construction process (based on search over graph structures) implemented in answer-set programming. We emphasise and demonstrate: complete system implementation, scalability, and robust performance & integration with industry-scale architecture industry tools (e.g., Revit, Archi-CAD) & standards (BIM, IFC).