id |
ecaade2020_130 |
authors |
Markusiewicz, Jacek and Gortazar Balerdi, Ander |
year |
2020 |
title |
LOTI - Using Machine Learning to simulate subjective opinions in design. |
source |
Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 439-448 |
doi |
https://doi.org/10.52842/conf.ecaade.2020.1.439
|
summary |
The objective of the workshop described in the article was to redesign a chair called Loti. In a subjective opinion shared by the authors and the participants of the workshop, the chair seems plagiarism of a famous chair by Ray and Charles Eames. The authors centralised the workshop on the use of computational tools for assessing subjective opinions. The authors and the participants created a method for detecting plagiarism and implemented it in the process of design. They created a parametric model of the chair that allowed changing the chair's components with variables. Using this model, the participants generated multiple variations and surveyed other students to assess which of the versions seemed plagiarism. With the information obtained from the survey, we trained a neural network to relate the variables with the level of plagiarism. We linked the parametric model with the neural network to create a tool that informs the user about the probability of committing plagiarism in real-time. The participants used the tool for designing new chairs to evaluate the efficiency of the method. |
keywords |
parametric design; machine learning; interfaces |
series |
eCAADe |
email |
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full text |
file.pdf (6,378,846 bytes) |
references |
Content-type: text/plain
|
Ackerman, JS (2002)
Origins, imitation, conventions : representation in the visual arts.
, MIT Press
|
|
|
|
Benoudjit, A, Derix, C and Coates, P (2004)
Human perception and space classification: The Perceptive Network
, Proceedings of the Generative Arts conference, Milan
|
|
|
|
Bush, V (1945)
As We May Think
, The Atlantic Monthly, 176(1), pp. 101-108
|
|
|
|
Chaillou, S (2019)
AI + Architecture | Towards a New Approach
, Master's Thesis, Harvard University
|
|
|
|
Draper, NR and Smith, H (1998)
Applied Regression Analysis
, Wiley John + Sons
|
|
|
|
Eco, U (1992)
The Original and the Copy
, Varela, FJ and Dupuy, JP (eds), Understanding Origins, Springer Netherlands
|
|
|
|
Gordon, AD (1999)
Classification
, Chapman & Hall
|
|
|
|
Karoji, G, Hotta, K, Hotta, A and Ikeda, Y (2019)
Pedestrian Dynamic Behaviour Modeling - An application to commercial environment using RNN framework
, Intelligent & Informed - Proceedings of the 24th CAADRIA Conference
|
|
|
|
Kingma, D and Ba, J (2015)
Adam: A method for stochastic optimization
, International Conference on Learning Representations, San Diego
|
|
|
|
Kinugawa, H and Takizawa, A (2019)
Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images
, Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference
|
|
|
|
Licklider, JCR (1960)
Man-Computer Symbiosis
, IRE Transactions on Human Factors in Electronics, HFE, pp. 4-11
|
|
|
|
Markusiewicz, J and Krężlik, A (2017)
Human-driven and machine-driven decisions in urban design and architecture - A comparison of two different methods in finding solutions to a complex problem
, ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Rome, pp. 505-514
|
|
|
|
Negroponte, N (1973)
The Architecture Machine
, MIT Press
|
|
|
|
Pedregosa, F, Varoquaux, G, Gramfort, A, Michel, V, Thirion, B, Grisel, O, Blondel, M, Prettenhofer, P, Weiss, R, Dubourg, V, Vanderplas, J, Passos, A, Cournapeau, D, Brucher, M, Perrot, M and Duchesnay, E (2011)
Scikit-learn: Machine Learning in Python
, Journal of Machine Learning Research, 12, pp. 2825-2830
|
|
|
|
Rumelhart, D, Hinton, G and Williams, R (1986)
Learning representations by back-propagating errors
, Nature, 323, pp. 533-536
|
|
|
|
Silva, NF and Bridges, AH (1997)
Human-Computer Interaction and Neural Networks in Architectural design A Tool for Design Exploration
, CAAD Futures, Munich
|
|
|
|
Zhang, Y, Grignard, A, Aubuchon, A, Lyons, K and Larson, K (2018)
Machine Learning for Real-time Urban Metrics and Design Recommendations
, ACADIA // 2018: Recalibration. On imprecision and infidelity.
|
|
|
|
last changed |
2022/06/07 07:59 |
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