Modelling space perception in urban planning: A cognitive AI-based approach

The study deals with cooperative space conceptualization by humans according to the AI-based cognitive approach and the urban-planning approach of architects and planners. It carries out the diagnosis and the control of example spaces in known urban environments. The paper is oriented toward suggesting system architectures to let spatial agents add structuring degrees to navigated urban spaces and challenge relevant disorientation conditions. The methodology draws on ontology-based text-mining analysis and statistical interpretation applied to university-class questionnaire surveys, exploring behaviours in human interaction with a space. After an introduction, a case-based discussion of the cooperative conceptualization and representation of space is carried out. The third section shows the ontological results of the case-study, with general results and follow-up discussed in the concluding section.