The proposed research aims at assessing a new modelling approach involving both human and artificial intelligences to decode and encode meaningful architectonic articulations from visuo-semantic tokens and neural responses as a next generation of grammar-less methods and based on information-communication technology (ICT) and cognitive science (CS) paradigms. By the use of multimodal brain-computer interfaces (BCI), it will elaborate progressively a technical infrastructure, allowing for producing and evaluating visuo-spatial and physical experiments and to finally reflect upon a synthetic and theoretical framework for architectural modelling. As a Use-Inspired Basic Research project, it aims at establishing significant basic theoretical and technical knowledge which, by its modalities, might also address consequently a much larger audience than expert practitioners and allow for a wide array of use cases. Once completed, it would represent an ideal ground for near-future implementations through further technology transfer mechanisms.
The project's schedule is organised along two main phases in a progressive and iterative fashion. While the first phase consists of integrating pluridisciplinary technical and theoretical knowledge from the broad fields of CS and ICT into Computer-Aided Architectural Design (CAAD), the second phase will focus on implementing learned methods and models to apply them on the modelling of architectural prototypes at small scale. Each conducted experiments will be comprised of several parts of shifting importance in time: signal acquisition and processing, generation and visual presentation of stimuli, discriminative and generative machine learning models, CAAD implementations.
The proposed research aims at assessing a new architectural modelling approach involving both human and artificial intelligences to decode and encode meaningful architectonic articulations from generated visuo-semantic tokens and neural responses as a next generation of grammar-less modelling methods, and based on information-communication technology and cognitive sciences paradigms. By the use of multimodal, gaze-dependent brain-computer interfaces, it will progressively elaborate a technical infrastructure for human-Machine-interaction, to allow for producing and evaluating visuo-spatial and physical experiments, and to finally reflect upon a synthetic and theoretical framework for the application of such methods.
Last updated:08.03.2023
