Cumincad : CUMINCAD Papers : Search Results

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
References

Hits 1 to 20 of 1809

Reformat results as: short short into frame detailed detailed into frame

_id	ecaade2018_303
id	ecaade2018_303
authors	Werner, Liss C.
year	2018
title	Biological Computation of Physarum - From DLA to spatial adaptive Voronoi
doi	https://doi.org/10.52842/conf.ecaade.2018.2.531
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 531-536
summary	Physarum polycephalum, also called slime mold or myxamoeba, has started attracting the attention of those architects, urban designers, and scholars, who work in experimental trans- and flexi-disciplines between architecture, computer sciences, biology, art, cognitive sciences or soft matter; disciplines that build on cybernetic principles. Slime mold is regarded as a bio-computer with intelligence embedded in its physical mechanisms. In its plasmodium stage, the single cell organism shows geometric, morphological and cognitive principles potentially relevant for future complexity in human-machines-networks (HMN) in architecture and urban design. The parametric bio-blob presents itself as a geometrically regulated graph structure-morphologically adaptive, logistically smart. It indicates cognitive goal-driven navigation and the ability to externally memorize (like ants). Physarum communicates with its environment. The paper introduces physarum polycephalum in the context of 'digital architecture' as a biological computer for self-organizing 2D- to 4D-geometry generation.
keywords	generative geometry; bio-computation; Voronoi
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ijac201816406
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
email
last changed	2019/08/07 14:04

_id	sigradi2018_1637
id	sigradi2018_1637
authors	Hosni, Cássia; Prata, Didiana; Ferrari, Erica; Lavigne, Nathalia
year	2018
title	Museum of the Underway Artists - Metanarratives on Networks
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1167-1172
summary	This article draws attention to an experience of workshop Masp.Etc.Br carried out by the Research Group Aesthetics of Memory of the 21st Century at the São Paulo Museum of Art (MASP), in which an aesthetic mapping of Paulista Avenue was done to discuss collaborative processes of image production organized through hashtags. The material gathered was an ample set of images posted on Instagram. After two collaborative edition processes, a final version was projected as a video at the free span of the Museum. These experiences bring attention to the aesthetics of the database and narratives in social networks.
keywords	São Paulo Museum of Art; MASP; Paulista Avenue; Public space; Database Aesthetics
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
doi	https://doi.org/10.52842/conf.acadia.2018.156
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 156-165
summary	With the development of information technology, the ideas of programming and mass calculation were introduced into the design field, resulting in the growth of computer- aided design. With the idea of designing by data, we began to manipulate data directly, and interpret data through design works. Machine Learning as a decision making tool has been widely used in many fields. It can be used to analyze large amounts of data and predict future changes. Generative Adversarial Network (GAN) is a model framework in machine learning. It’s specially designed to learn and generate output data with similar or identical characteristics. Pix2pixHD is a modified version of GAN that learns image data in pairs and generates new images based on the input. The author applied pix2pixHD in recognizing and generating architectural drawings, marking rooms with different colors and then generating apartment plans through two convolutional neural networks. Next, in order to understand how these networks work, the author analyzed their framework, and provided an explanation of the three working principles of the networks, convolution layer, residual network layer and deconvolution layer. Lastly, in order to visualize the networks in architectural drawings, the author derived data from different layer and different training epochs, and visualized the findings as gray scale images. It was found that the features of the architectural plan drawings have been gradually learned and stored as parameters in the networks. As the networks get deeper and the training epoch increases, the features in the graph become more concise and clearer. This phenomenon may be inspiring in understanding the designing behavior of humans.
keywords	full paper, design study, generative design, ai + machine learning, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:49

_id	ecaade2018_158
id	ecaade2018_158
authors	Zhou, Jing, Klumpner, Hubert and Brillembourg, Afredo
year	2018
title	The Dynamic Geometric Network Model for Representing Verticalized Urban Environment and its Generation
doi	https://doi.org/10.52842/conf.ecaade.2018.1.525
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 525-530
summary	Against the background of urbanization and the fast growth of population in big cities, there will be more and more high-rises emerged in the future. In some big cities, the various layers of public transpiration networks such as metro systems also played an essential role in the urban life. In the verticalized urban environment, the complexity of the multi-layers space system connected by various horizontal and vertical connections have been beyond people's cognition. The boundaries between private space and public space, outdoor-space and indoor-space have already blurred. The graph theory based urban spatial analysis approaches are adopted in urban studies to tackle with the urban complexity issues. However, at present, most of the methods proposed are specializing in open urban spaces, and they cannot describe the three-dimensional completely and accurately. Therefore, in this paper, a new graph theory based representation method, the Dynamic Geometric Network Model, which adapted to the verticalized urban environment will be proposed. And the approach of how to automatically generate such a representation model according to the urban layout will also be introduced.
keywords	Graph Model Representation; Graph Model Generation; Verticalized Urban Environment
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ecaade2018_232
id	ecaade2018_232
authors	Al Bondakji, Louna, Chatzi, Anna-Maria, Heidari Tabar, Minoo, Wesseler, Lisa-Marie and Werner, Liss C.
year	2018
title	VR-visualization of High-dimensional Urban Data
doi	https://doi.org/10.52842/conf.ecaade.2018.2.773
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 773-780
summary	The project aims to investigate the possibility of VR in a combination of visualizing high-dimensional urban data. Our study proposes a data-based tool for urban planners, architects, and researchers to 3D visualize and experience an urban quarter. Users have a possibility to choose a specific part of a city according to urban data input like "buildings, streets, and landscapes". This data-based tool is based on an algorithm to translate data from Shapefiles (.sh) in a form of a virtual cube model. The tool can be scaled and hence applied globally. The goal of the study is to improve understanding of the connection and analysis of high-dimensional urban data beyond a two-dimensional static graph or three-dimensional image. Professionals may find an optimized condition between urban data through abstract simulation. By implementing this tool in the early design process, researchers have an opportunity to develop a new vision for extending and optimizing urban materials.
keywords	Abstract Urban Data Visualization; Virtual Reality; Geographical Information System
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2018_389
id	ecaade2018_389
authors	Algeciras-Rodriguez, Jose
year	2018
title	Stochastic Hybrids - From references to design options through Self-Organizing Maps methodology.
doi	https://doi.org/10.52842/conf.ecaade.2018.1.119
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 119-128
summary	This ongoing research aims to define a general assisted design method to offer non-trivial design options, where form is produced by merging characteristics from initial reference samples collection that serves as an input set. This project explores design processes laying on the use of non-linear procedures and experiments with Self-Organizing Map (SOM), as neural networks algorithms, to generate geometries. All processes are applied to a set of models representing classic sculpture, whose characteristics are encoded by the SOM process. The result of it is a set of new geometry resembling characteristics from the original references. This method produces hybrid forms that acquire characteristics from several input references. The resulting hybrid entities are intended to be non-trivial solutions to specific design situations, so far, at the stage of this research, mainly formal requirements.
keywords	Self-Orgnizing Maps; Cognitive Space; Design Options; Form Finding; Artificial Intelligence
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2018_1671
id	sigradi2018_1671
authors	Brito, Michele; de Sá, Ana Isabel; Borges, Jéssica; Rena, Natacha
year	2018
title	IndAtlas - Technopolitic platform for urban investigation
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1305-1312
summary	This article presents the project of the urban research platform IndAtlas, currently in early development stage by UFMG’s Research Group Indisciplinar. Through the association of crowdsourcing tools, a spatial database and the production of visualizations of different types, it is intended to create a Web platform for collecting, analyzing and depicting information about processes of production and transformation of urban space. It is proposed that the phenomena (themes) investigated in the platform are approached mainly from four axes: 1) spatial / territorial; 2) temporal; 3) social; 4) communicational. To do this, we try to combine online collaborative maps with the production of dynamic timelines and visualizations of networks of social actors (graphs), connected with social networks and Wiki pages. The article will address the development of Indisciplinar’s working method, which guided the proposal of the platform, as well as the functional and technical aspects to be observed for its implementation, the proposed architecture and the importance of interoperability for the project. Finally, the inquiries derived from the first test experiment of an IndAtlas test prototype will be presented. The experiment took place in a workshop belonging to the Cidade Eletrônika 2018 Festival – an arts and technology event. The workshop was offered in January of the same year, and it proposed a collaborative cartography of the Santa Tereza neighborhood, in Belo Horizonte / MG – a traditional neighborhood of great importance for historical heritage, currently subject to great real estate pressure and the focus of a series of territorial disputes.
keywords	IndAtlas, Crowdsourcing, Urban Technopolitics,, Digital Cartographies,, Spatial Data.
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	caadria2021_089
id	caadria2021_089
authors	Cristie, Verina, Ibrahim, Nazim and Joyce, Sam Conrad
year	2021
title	Capturing and Evaluating Parametric Design Exploration in a Collaborative Environment - A study case of versioning for parametric design
doi	https://doi.org/10.52842/conf.caadria.2021.2.131
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 131-140
summary	Although parametric modelling and digital design tools have become ubiquitous in digital design, there is a limited understanding of how designers apply them in their design processes (Yu et al., 2014). This paper looks at the use of GHShot versioning tool developed by the authors (Cristie & Joyce, 2018; 2019) used to capture and track changes and progression of parametric models to understand early-stage design exploration and collaboration empirically. We introduce both development history graph-based metrics (macro-process) and parametric model and geometry change metric (micro-process) as frameworks to explore and understand the captured progression data. These metrics, applied to data collected from three cohorts of classroom collaborative design exercises, exhibited students' distinct modification patterns such as major and complex creation processes or minor parameter explorations. Finally, with the metrics' applicability as an objective language to describe the (collaborative) design process, we recommend using versioning for more data-driven insight into parametric design exploration processes.
keywords	Design exploration; parametric design; history recording; version control; collaborative design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_139
id	ecaade2018_139
authors	Cudzik, Jan and Radziszewski, Kacper
year	2018
title	Artificial Intelligence Aided Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.2018.1.077
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 77-84
summary	Tools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools that suit their specific needs. In some cases, they use artificial intelligence. Despite many similarities, they have different advantages and disadvantages. Therefore the change in the design process is more visible and unseen before solution are brought in the discipline. The article presents methods of applying the selected artificial intelligence algorithms: swarm intelligence, neural networks and evolutionary algorithms in the architectural practice by authors. Additionally research shows the methods of analogue data input and output approaches, based on vision and robotics, which in future combined with intelligence based algorithms, might simplify architects everyday practice. Presented techniques allow new spatial solutions to emerge with relatively simple intelligent based algorithms, from which many could be only accomplished with dedicated software. Popularization of the following methods among architects, will result in more intuitive, general use design tools.
keywords	computer aideed design; artificial intelligence,; evolutionary algorithms; swarm behaviour; optimization; parametric design
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2018_292
id	ecaade2018_292
authors	Dennemark, Martin, Aicher, Andreas, Schneider, Sven and Hailu, Tesfaye
year	2018
title	Generative Hydrology Network Analysis - A parametric approach to water infrastructure based urban planning
doi	https://doi.org/10.52842/conf.ecaade.2018.2.327
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 327-334
summary	Urban water systems need to be dimensioned well to be economical and distribute water in a good quality to all consumers. Their pipe sizes are dependent on demand and location of consuming nodes. Within uncertain development of cities, planning sustainable hydraulic networks is challenging. This paper explores, how the definition of urban design parameters can be supported using parametric urban design models and computational water network analysis. For the latter we developed new components for Grasshopper based on the open accessible water analysis tool EPANET. In two example cases we demonstrate potential applications of this tool for water-sensitive planning of emerging cities to find optimal positions for water sources or pipe diameters. In subsequent research, this could be used to derive probability-based recommendations for the dimensioning of a water network within uncertain growth.
keywords	water infrastructure; urban planning; parametric design; uncertainty; emerging cities
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2018_210
id	ecaade2018_210
authors	Ezzat, Mohammed
year	2018
title	A Computational Tool for Mapping the Users' Urban Cognition - A Framework and a Representation for the Evolutionary Optimization of the Fuzzy Binary Relation between the Urban Conceptions of "Us" and "Others"
doi	https://doi.org/10.52842/conf.ecaade.2018.1.667
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 667-676
summary	The paper proposes a computational tool for simulating the users' urban cognitive systems, or more specifically the long-term memory associated with the knowledge of urbanism and its related urban visual features. The tool builds on our comprehensive theory of Urbanism, which presents a monolithic, structured, comprehensive, professional conception of Urbanism based on which any relativistic users' urban conceptions could be predicted as a restructuring of the professional conception. These versatile relativistic conceptions would emerge based on a nurturing environment, which is a conception of the empirical/anthropological collected data of the intended users' reflections against their preferred constructed urban environments. Once the users' conceptions of Urbanism are formulated, which is the first phase of the simulation, the users' impressions against any examined urban constructs are attainable, which is the second phase of the simulation. The two phases, the framework, would be monolithically represented by a proposed novel cellular graph. The proposed computational tool is thought of as a robust technique for the computational incorporation of the users' urban identity, and some of its constituents could be considered as a needed common platform of communication for a successful Human-Computer interaction in the field of urban analysis/design.
keywords	a comprehensive model of Urbanism; a default professional conception of Urbanism; the relativistic users' conceptions of Urbanism ; recognized extracted urban features ; the users' urban identity; A comprehensive theory for space syntax:
series	eCAADe
email
last changed	2022/06/07 07:55

_id	sigradi2018_1772
id	sigradi2018_1772
authors	Farias, Ana C. C; Paio, Alexandra
year	2018
title	Technopolitics and participatory processes - Interactions between digital networks and streets in Lisbon
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1321-1327
summary	This article presents a survey and analysis of the technopolitical devices created in projects of local initiatives carried out in Lisbon, within the scope of the Neighborhoods and Zones of Priority Intervention program, of the City Council. The methodology adopted is based on the reading of the projects, analysis of the technopolitics encountered and interviews with representatives of the entities that proposed them. In this way, it was possible to observe tendencies, potentialities and difficulties faced in the proposal and use of technopolitics in the scope of these projects, which allowed to conclude that the digital dimension has an important role in the reinforcement and expansion of an existing articulation in the territories, between partner entities and communities.
keywords	Technopolitics; Lisbon; observatory; community-based action; digital technology
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	ijac201816201
id	ijac201816201
authors	Harding, John and Cecilie Brandt-Olsen
year	2018
title	Biomorpher: Interactive evolution for parametric design
source	International Journal of Architectural Computing vol. 16 - no. 2, 144-163
summary	Combining graph-based parametric design with metaheuristic solvers has to date focused solely on performance-based criteria and solving clearly defined objectives. In this article, we outline a new method for combining a parametric modelling environment with an interactive Cluster-Orientated Genetic Algorithm. In addition to performance criteria, evolutionary design exploration can be guided through choice alone, with user motivation that cannot be easily defined. As well as numeric parameters forming a genotype, the evolution of whole parametric definitions is discussed through the use of genetic programming. Visualisation techniques that enable mixing small populations for interactive evolution with large populations for performance-based optimisation are discussed, with examples from both academia and industry showing a wide range of applications.
keywords	Design exploration, genetic programming, human–computer interaction, interactive genetic algorithms, k-means clustering, parametric design
series	journal
email
last changed	2019/08/07 14:03

_id	ecaade2018_280
id	ecaade2018_280
authors	Herthogs, Pieter, Tunçer, Bige, Schläpfer, Markus and He, Peijun
year	2018
title	A Weighted Graph Model to Estimate People's Presence in Public Space - The Visit Potential Model
doi	https://doi.org/10.52842/conf.ecaade.2018.2.611
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 611-620
summary	In this paper, we introduce the Visit Potential Model (VPM), an integrated model to evaluate public space characteristics. It is an initial attempt to model and predict the potential presence of people in public places (i.e. their Visit Potential); the presence and flux of people being the underlying driver of all public space. We achieved this by combining a proposed universal law of visit frequencies in cities with a gravity measure for accessibility. We also demonstrate how this model can be extended to represent public space quality and liveliness throughout the hours of the day - a crucial concept in public space design. The paper primarily discusses the development of the calculation model, describing three variants to calculate Visit Potential values for public spaces: based on a public space's accessibility to people, the potential number of people visiting attractors, and the number of people moving through and occupying a public space.
keywords	public space quality; liveliness; weighted graphs; accessibility; walkability
series	eCAADe
email
last changed	2022/06/07 07:50

_id	acadia20_382
id	acadia20_382
authors	Hosmer, Tyson; Tigas, Panagiotis; Reeves, David; He, Ziming
year	2020
title	Spatial Assembly with Self-Play Reinforcement Learning
doi	https://doi.org/10.52842/conf.acadia.2020.1.382
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 382-393.
summary	We present a framework to generate intelligent spatial assemblies from sets of digitally encoded spatial parts designed by the architect with embedded principles of prefabrication, assembly awareness, and reconfigurability. The methodology includes a bespoke constraint-solving algorithm for autonomously assembling 3D geometries into larger spatial compositions for the built environment. A series of graph-based analysis methods are applied to each assembly to extract performance metrics related to architectural space-making goals, including structural stability, material density, spatial segmentation, connectivity, and spatial distribution. Together with the constraint-based assembly algorithm and analysis methods, we have integrated a novel application of deep reinforcement (RL) learning for training the models to improve at matching the multiperformance goals established by the user through self-play. RL is applied to improve the selection and sequencing of parts while considering local and global objectives. The user’s design intent is embedded through the design of partial units of 3D space with embedded fabrication principles and their relational constraints over how they connect to each other and the quantifiable goals to drive the distribution of effective features. The methodology has been developed over three years through three case study projects called ArchiGo (2017–2018), NoMAS (2018–2019), and IRSILA (2019-2020). Each demonstrates the potential for buildings with reconfigurable and adaptive life cycles.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	lasg_whitepapers_2019_133
id	lasg_whitepapers_2019_133
authors	Ji, Haru Hyunkyung; and Graham Wakefield
year	2019
title	Selected Artificial Natures, 2017-2018
source	Living Architecture Systems Group White Papers 2019 [ISBN 978-1-988366-18-0] Riverside Architectural Press: Toronto, Canada 2019. pp.133 - 142
summary	Artificial Nature is a research-creation collaboration co-founded by Haru Hyunkyung Ji and Graham Wakefield in 2007. It has led to a decade of immersive installations in which the invitation is to become part of an alien ecosystem rich in feedback networks.1 Here we present four recent works in this series between 2017 and 2018.
keywords	living architecture systems group, organicism, intelligent systems, design methods, engineering and art, new media art, interactive art, dissipative systems, technology, cognition, responsiveness, biomaterials, artificial natures, 4DSOUND, materials, virtual projections,
email
last changed	2019/07/29 14:02

_id	ecaade2018_353
id	ecaade2018_353
authors	Juzwa, Nina and Krotowski, Tomasz
year	2018
title	Sketch - Computer - Imagination - Reflections on Architecture Education Methodology
doi	https://doi.org/10.52842/conf.ecaade.2018.1.583
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 583-588
summary	The article underlines the problem of introducing computer techniques into the education process in master degree studies in architecture. Following the consumer society, developing technologies, changing social values architecture education changed its continuous principle into two-level system. The system well known from other fields of education results in diversified level of knowledge between admitted students on master studies. This fact in together with large exercise groups and a relatively short time allocated with the project requires methodical approach in relationship between a student and a teacher. The article focuses on complexity of a design process within different stages. Special attention is placed to an early design phase of shaping an architecture form because it demands different ways of presentation including freehand sketching, physical modelling and digital modelling. These tools correspond to the subsequent three phases of the design process, starting with exploration of the idea and context, functional decisions and determining the aesthetics. In authors opinion, the first phase of teaching process held without the use of computer techniques led to a higher originality of the architecture concept and increased efficiency in design process.
keywords	sketch; computer ; architect's vision; shaping the architecture
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2018_111
id	ecaade2018_111
authors	Khean, Nariddh, Fabbri, Alessandra and Haeusler, M. Hank
year	2018
title	Learning Machine Learning as an Architect, How to? - Presenting and evaluating a Grasshopper based platform to teach architecture students machine learning
doi	https://doi.org/10.52842/conf.ecaade.2018.1.095
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 95-102
summary	Machine learning algorithms have become widely embedded in many aspects of modern society. They have come to enhance systems, such as individualised marketing, social media services, and search engines. However, contrasting its growing ubiquity, the architectural industry has been comparatively resistant in its adoption; objectively one of the slowest industries to integrate with machine learning. Machine learning expertise can be separate from professionals in other fields; however, this separation can be a major hinderance in architecture, where interaction between the designer and the design facilitates the production of favourable outcomes. To bridge this knowledge gap, this research suggests that the solution lies with architectural education. Through the development of a novel educative framework, the research aims to teach architecture students how to implement machine learning. Exploration of student-centred pedagogical strategies was used to inform the conceptualisation of the educative module, which was subsequently implemented into an undergraduate computational design studio, and finally evaluated on its ability to effectively teach designers machine learning. The developed educative module represents a step towards greater technological adoption in the architecture industry.
keywords	Artificial Intelligence; Machine Learning; Neural Networks; Student-Centred Learning; Educative Framework
series	eCAADe
email
last changed	2022/06/07 07:52

_id	caadria2018_126
id	caadria2018_126
authors	Khean, Nariddh, Kim, Lucas, Martinez, Jorge, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2018
title	The Introspection of Deep Neural Networks - Towards Illuminating the Black Box - Training Architects Machine Learning via Grasshopper Definitions
doi	https://doi.org/10.52842/conf.caadria.2018.2.237
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 237-246
summary	Machine learning is yet to make a significant impact in the field of architecture and design. However, with the combination of artificial neural networks, a biologically inspired machine learning paradigm, and deep learning, a hierarchical subsystem of machine learning, the predictive capabilities of machine learning processes could prove a valuable tool for designers. Yet, the inherent knowledge gap between the fields of architecture and computer science has meant the complexity of machine learning, and thus its potential value and applications in the design of the built environment remain little understood. To bridge this knowledge gap, this paper describes the development of a learning tool directed at architects and designers to better understand the inner workings of machine learning. Within the parametric modelling environment of Grasshopper, this research develops a framework to express the mathematic and programmatic operations of neural networks in a visual scripting language. This offers a way to segment and parametrise each neural network operation into a basic expression. Unpacking the complexities of machine learning in an intermediary software environment such as Grasshopper intends to foster the broader adoption of artificial intelligence in architecture.
keywords	machine learning; neural network; action research; supervised learning; education
series	CAADRIA
email
last changed	2022/06/07 07:52

For more results click below: