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 |
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Title of host publication | Artificial Intelligence in Performance-Driven Design |
Subtitle of host publication | Theories, Methods, and Tools |
Editors | Narjes Abbasabadi, Mehdi Ashayeri |
Publisher | Wiley-Liss Inc. |
Chapter | 1 |
Pages | 1-30 |
Number of pages | 30 |
ISBN (Electronic) | 9781394172092 |
ISBN (Print) | 9781394172061 |
DOIs | |
Publication status | Published - Apr 2024 |
Bibliographical note
Publisher Copyright:© 2024 by John Wiley & Sons, Inc. All rights reserved.