Resumen de Artificial Intelligence in Architecture: A Journey from Engineering Applications to Generative Design and Conceptual Representations of Space
Jaime de Miguel Rodríguez
This thesis explores the role of Artificial Intelligence (AI) in the conceptual modelling of space, focusing on architectural aesthetics, or 'venustas', while also addressing 'utilitas' (functionality) and 'firmitas' (structure). The aesthetic aspect, which is the most challenging, is central to the research, which examines the interplay between AI, design aesthetics, and spatial representations. It examines the challenges and opportunities that AI presents for creativity, conceptual reasoning, and the representation of space - three pillars that are central to architectural discourse.
Various AI techniques are analysed, including neural networks for structural applications in civil and seismic engineering, and generative models for urban analysis and form-finding. Formal Concept Analysis is introduced as a key tool for conceptual modelling in AI, applied to urban case studies. The thesis continues by critically analysing generative AI models, evaluating their creative potential, their capacity to handle complex and ambiguous representations, and their suitability to perform at a conceptual level. Although generative AI shows promise in generating creative design solutions, it is limited in performing concept-driven operations, particularly compared to symbolic models that excel in reasoning, composability, and explainability.
The research finally delves into the problem of spatial representation in architectural design. A variety of symbolic and neural-symbolic approaches are reviewed, yet none fully address the complex, qualitative aspects of space central to human cognition and architectural practice. In response, this thesis proposes a novel proof-of-concept model that revisits purely symbolic approaches. This model provides a foundation for emerging conceptual structures from raw sensory data, addressing the long-standing symbol grounding problem in AI and offering a potential solution for representing spatial objects in architectural design.
Ultimately, this thesis contributes to the growing dialogue between AI and architectural design by proposing a new framework for integrating AI into the creative and conceptual processes that define the discipline. It offers a critical assessment of current AI methods and suggests a novel approach that could pave the way for future advancements in AI and Design.
