Abstract
This chapter presents methodological reflections on the necessity and utility of artificial intelligence (AI) 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 their consequences for mapping and navigating such a complex decision space. This chapter will discuss promising directions in AI for augmenting decision-making processes in architectural design for mapping and navigating complex design spaces.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence in Performance-Driven Design |
| Subtitle of host publication | Theories, Methods, and Tools |
| Editors | Narjes Abbasabadi, Mehdi Ashayeri |
| Place of Publication | Hoboken, NJ |
| Publisher | Wiley |
| Chapter | 1 |
| Pages | 1-30 |
| Number of pages | 30 |
| ISBN (Electronic) | 9781394172085, 9781394172078 |
| ISBN (Print) | 9781394172061 |
| DOIs | |
| Publication status | Published - 2024 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.