Augmented Computational Design: Methodical Application of Artificial Intelligence in Generative Design
This work addresses the problem of decision-making in architectural design for professionals, but it is incremental as it builds on existing generative design paradigms.
The paper tackles the challenge of enhancing generative design processes in architecture by using artificial intelligence to manage numerous small decisions and link them to performance outcomes, aiming to map and navigate complex design spaces effectively.
This chapter presents methodological reflections on the necessity and utility of artificial intelligence in generative design. Specifically, the chapter discusses how generative design processes can be augmented by AI to deliver in terms of a few outcomes of interest or performance indicators while dealing with hundreds or thousands of small decisions. The core of the performance-based generative design paradigm is about making statistical or simulation-driven associations between these choices and consequences for mapping and navigating such a complex decision space. This chapter will discuss promising directions in Artificial Intelligence for augmenting decision-making processes in architectural design for mapping and navigating complex design spaces.