Semantic knowledge in generation of 3D layouts for decision-making
Luca Caneparo
Abstract
Generative computation has the potential to enhance the accuracy, effectiveness, and creativity of spatial layout in design and planning. The paper proposes a methodology to separate the knowledge about objects, spatial relationships, and constraints from the generative process. The separation between the knowledge in a domain and its possible practical uses is an important achievement of semantic technologies, because it grants access to a large body of knowledge, spanning various aspects and processes across buildings and cities, which is being codified into formal ontologies. The present study has reused existing knowledge from two established ontologies. An illustrative case-project demonstrates the suitability of the methodology for a complex layout planning problem, involving a large number of decision-makers, with multiple competing objectives and criteria. The system implements multidimensional visual interactive tools to assist designers, planners, and decision-makers in exploring the layouts and the criteria, to develop their confidence in what qualifies as a good and effective solution.