CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
id ijac201816406
authors As, Imdat; Siddharth Pal and Prithwish Basu
year 2018
title Artificial intelligence in architecture: Generating conceptual design via deep learning
source International Journal of Architectural Computing vol. 16 - no. 4, 306-327
summary Artificial intelligence, and in particular machine learning, is a fast-emerging field. Research on artificial intelligence focuses mainly on image-, text- and voice-based applications, leading to breakthrough developments in self-driving cars, voice recognition algorithms and recommendation systems. In this article, we present the research of an alternative graph- based machine learning system that deals with three-dimensional space, which is more structured and combinatorial than images, text or voice. Specifically, we present a function-driven deep learning approach to generate conceptual design. We trained and used deep neural networks to evaluate existing designs encoded as graphs, extract significant building blocks as subgraphs and merge them into new compositions. Finally, we explored the application of generative adversarial networks to generate entirely new and unique designs.
keywords Architectural design, conceptual design, deep learning, artificial intelligence, generative design
series journal
full text file.pdf ( bytes)
references Content-type: text/plain
Details Citation Select
100%; open Alexander C. (1977) Find in CUMINCAD A pattern language: towns, building, construction , Oxford: Oxford University Press

100%; open Boyer J.M. and Myrvold W.J. (2004) Find in CUMINCAD On the cutting edge: simplified O(n) planarity by edge addition , J Graph Algorithm Appl; 8(3): 241–273

100%; open Chen X., Duan Y., Houthooft R. et al. (2016) Find in CUMINCAD InfoGAN: interpretable representation learning by information maximizing generative adversarial nets , NIPS,

100%; open Cross N. (2011) Find in CUMINCAD Design thinking: understanding how designers think and work , Oxford: Bloomsbury Academic

100%; open De Haan H. (1988) Find in CUMINCAD Architects in competition: international architectural competitions of the last 200 years , London: Thames and Hudson

100%; open Duarte J.P. (2005) Find in CUMINCAD Towards mass customization of housing: the grammar of Siza’s houses at Malagueira , Environ Plann B; 32: 347e380

100%; open Duvenaud D., Maclaurin D., Aguilera-Iparraguirre J. et al. (2015) Find in CUMINCAD Convolutional networks on graphs for learning molecular fingerprints , Proceedings of the 28th international conference on neural information processing systems (NIPS), Montreal, QC, Canada, 7–12 December 2015, vol. 2

100%; open Ehrig H. and Kreowski H.-J. (1979) Find in CUMINCAD Pushout-properties: an analysis of gluing constructions for graphs , Math Nachr; 91: 135–149

100%; open Gropius W. (1970) Find in CUMINCAD Scope of total architecture , New York: Collier Books

100%; open Grover A. and Leskovec J. (2016) Find in CUMINCAD Node2vec: scalable feature learning for networks , Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (KDD ‘16), San Francisco, CA, 13–17 August 2016, pp. 855–864. New York: ACM. DOI:10.1145/2939672.2939754

100%; open Hagberg A., Schult D. and Swart P. (2005) Find in CUMINCAD NetworkX: Python software for the analysis of networks , Mathematical Modeling and Analysis, Los Alamos National Laboratory, Los Alamos, NM

100%; open He K., Zhang X., Ren S. et al. (2016) Find in CUMINCAD Deep residual learning for image recognition , IEEE conference on computer vision and pattern recognition (CVPR), Las Vegas, NV, 27–30 June 2016, pp. 770–778. New York: IEEE

100%; open Jabi W., Soe S., Theobald P. et al. (2017) Find in CUMINCAD Enhancing parametric design through non-manifold topology , Des Stud; 52: 96–114

100%; open Karras T., Aila T., Laine S. et al. (2018) Find in CUMINCAD Progressive growing of GANs for improved quality, stability, and variation , 6th international conference on learning representations (ICLR) , Vancouver, BC, Canada, 30 April–3 May 2018

100%; open Liao L., He X., Zhang H. et al. (2018) Find in CUMINCAD Attributed social network embedding , IEEE T Knowl Data En . Epub ahead of print 27 March 2018. DOI: 10.1109/TKDE.2018.2819980

100%; open Mitrovic B. (2011) Find in CUMINCAD Philosophy for architects , New York: Princeton Architectural Press

100%; open Ruiz-Montiel M., Boned J., Gavilanes J. et al. (2012) Find in CUMINCAD Design with shape grammars and reinforcement learning , Adv Eng Inform; 27: 230–245

100%; open Sjoberg C., Beorkrem C., Ellinger J. et al. (2017) Find in CUMINCAD Emergent syntax: machine learning for curation of design solution space , Proceedings Disruption Disciplines of the 37th Annual Conference of the Association for Computer Aided Design in Architecture, MIT, Cambridge, pp. 552–561

100%; open Steinfeld K. (2017) Find in CUMINCAD Dreams may come , Nagakura T. (ed.) Acadia 2017 disciplines & disruption: proceedings of the 37th annual conference of the Association for Computer Aided Design in Architecture. Cambridge: MIT, pp. 590–599

100%; open Stiny G. and Gips J. (1972) Find in CUMINCAD Shape grammars and the generative specification of painting and sculpture , Freiman CV (ed.) Information processing 71 . Amsterdam: North-Holland, pp. 1460–1465

last changed 2019/08/07 12:04
pick and add to favorite papersHOMELOGIN (you are user _anon_676091 from group guest) CUMINCAD Papers Powered by SciX Open Publishing Services 1.002