Collective Construction Modeling and Machine Learning: Potential for Architectural Design
Document Type
Conference Proceeding
Publication Date
1-1-2017
Abstract
Recently, there are significant developments in artificial intelligence using advanced machine learning algorithms such as deep neural networks. These new methods can defeat human expert players in strategy-based board games such as Go and video games such as Breakout. This paper suggests a way to incorporate such advanced computing methods into architectural design through introducing a simple conceptual design project inspired by computational interpretations of wasps' collective constructions. At this stage, the paper's intent is not to introduce a practical and fully finished tool directly useful for architectural design. Instead, the paper proposes an example of a program that can potentially become a conceptual framework for incorporating such advanced methods into architectural design.
Identifier
85101128705 (Scopus)
ISBN
[9789491207129]
Publication Title
Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe
ISSN
26841843
First Page
593
Last Page
600
Volume
1
Recommended Citation
Narahara, Taro, "Collective Construction Modeling and Machine Learning: Potential for Architectural Design" (2017). Faculty Publications. 9855.
https://digitalcommons.njit.edu/fac_pubs/9855
