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.
@article{arxiv.2310.09243,
title = {Augmented Computational Design: Methodical Application of Artificial Intelligence in Generative Design},
author = {Pirouz Nourian and Shervin Azadi and Roy Uijtendaal and Nan Bai},
journal= {arXiv preprint arXiv:2310.09243},
year = {2023}
}
Comments
This is the author's version of the book chapter Augmented Computational Design: Methodical Application of Artificial Intelligence in Generative Design. In Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools Towards Sustainability, edited by Narjes Abbasabadi and Mehdi Ashayeri. Wiley, 2023