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

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_id	sigradi2021_359
id	sigradi2021_359
authors	Carrasco-Walburg, Carolina, Valenzuela-Astudillo, Eduardo, Maino-Ansaldo, Sandro, Correa-Díaz, Matías and Zapata-Torres, Diego
year	2021
title	Experiential Teaching-learning Tools: Critical Study of Representational Media and Immersion in Architecture
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 475–488
summary	The use of Virtual Reality (VR) in teaching-learning process of design, theory and history of architecture has increased in terms of virtual tours. A preliminary study of techniques and capabilities of Immersive Virtual Reality (IVR) systems allowed us to establish that the immersive and interactive virtual experience facilitates the perception and enhancement of spatial qualities. In addition, it facilitates analysis since it promotes observation and the development of spatial thinking. However, the use of this medium as a tool for analysis is less frequent. Therefore, in this research we comparatively evaluate the impact that VR has on such a task. We developed an analysis instrument using experiential learning cycles that was tested with students in control and experimental groups. As a result, we found that the experience of inhabiting facilitates integration of fundamental concepts, allowing empirical evaluation of architecture and streamlining communication in the classroom as an active learning strategy.
keywords	Virtual Reality, Architecture, Spatial Perception, Experiential Learning, Teaching-Learning Process
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	sigradi2021_375
id	sigradi2021_375
authors	Banda, Pablo and Valenzuela-Astudillo, Eduardo
year	2021
title	Immersive Variations: Connecting Architectural Sensitivity with Parametric Design through Collaborative Virtual Reality Environments
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 1017–1028
summary	Undergraduate design studies for digital fabrication and non-standard architecture are complex as their participants are usually far from systems thinking and have a basic level of confidence in the use of advanced digital tools. Furthermore, in the face of high formal complexity, the understanding of the structural system and its effects for the inhabitant are not evident. This work presents an implementation of Virtual Reality to introduce Latin American architecture university students to digital fabrication and parametric design, taking as its main premise that during the initial design stage, the designed architecture using virtual reality techniques and spatial perception can engage students to appreciate the value in these new designs, formulating new arguments and paradigms to further contribute to their training as contemporary professionals.
keywords	irtual Reality, Digital fabrication, Architecture, Spatial Perception
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	acadia21_160
id	acadia21_160
authors	Cao, Shicong; Zheng, Hao
year	2021
title	A POI-Based Machine Learning Method in Predicting Health
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 160-169.
doi	https://doi.org/10.52842/conf.acadia.2021.160
summary	This research aims to explore the quantitative relationship between urban planning decisions and the health status of residents. By modeling the Point of Interest (POI) data and the geographic distribution of health-related outcomes, the research explores the critical factors in urban planning that could influence the health status of residents. It also informs decision-making regarding a healthier built environment and opens up possibilities for other data-driven methods. The data source constitutes two data sets, the POI data from OpenStreetMap, and the PLACES: Local Data for Better Health dataset from CDC. After the data is collected and joined spatially, a machine learning method is used to select the most critical urban features in predicting the health outcomes of residents. Several machine learning models are trained and compared. With the chosen model, the prediction is evaluated on the test dataset and mapped geographically. The relations between factors are explored and interpreted. Finally, to understand the implications for urban design, the impact of modified POI data on the prediction of residents' health status is calculated and compared. This research proves the possibility of predicting resident's health from urban conditions with machine learning methods. The result verifies existing healthy urban design theories from a different perspective. This approach shows vast potential that data could in future assist decision-making to achieve a healthier built environment.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	sigradi2021_381
id	sigradi2021_381
authors	El-Khouly, Tamer, Abdelmohsen, Sherif, Riad, Aya, Abdelkhalek, Joumana and Abdelgawad, Norhan
year	2021
title	Heritage-inspired Interactivity: Traditional Geometric Patterns as an Inspiration for Interactive Architectural Prototypes
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 617–628
summary	Coding and visual programming are becoming an important component of design education, with focus on algorithmic thinking, form finding, and generative design. Programming languages like Processing are increasingly explored within shape studies in architecture, thus opening unique possibilities for creative design exploration. Most pedagogical approaches that integrate coding in exploring heritage-inspired geometric patterns focus on shape grammars and rule-based design. This exploratory paper further examines the potential of traditional geometric patterns as inspiration sources for interactivity in architectural design. We discuss the process and outcomes of an undergraduate architectural computing course at the American University in Cairo, Egypt, where students implement visual programming using Processing to develop interactive architecture prototypes based on cultural heritage. Results demonstrated a variety of abstraction and translation strategies for both tangible and intangible heritage inspirations, and generation of emergent concepts for diverse architectural prototypes including urban grids, movable structures, and responsive façades.
keywords	Generative design, programming, pattern generation, heritage, interactivity
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	caadria2021_391
id	caadria2021_391
authors	Elshani, Diellza, Koenig, Reinhard, Duering, Serjoscha, Schneider, Sven and Chronis, Angelos
year	2021
title	Measuring Sustainability and Urban Data Operationalization - An integrated computational framework to evaluate and interpret the performance of the urban form.
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. 407-416
doi	https://doi.org/10.52842/conf.caadria.2021.2.407
summary	With rapid urbanization, the necessity for sustainable development has skyrocketed, and sustainable urban development is a must. Recent advances in computing performance of urban layouts in real-time allow for new paradigms of performance-driven design. As beneficial as utilizing multiple layers of urban data may be, it can also create a challenge in interpreting and operationalizing data. This paper presents an integrated computational framework to measure sustainability, operationalize and interpret the urban forms performance data using generative design methods, novel performance simulations, and machine learning predictions. The performance data is clustered into three pillars of sustainability: social, environmental, and economical, and it is followed with the performance space exploration, which assists in extracting knowledge and actionable rules of thumb. A significant advantage of the framework is that it can be used as a discussion table in participatory planning processes since it could be easily adapted to interactive environments.
keywords	generative design; data interpretation ; urban sustainability; performance simulation; machine learning
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ascaad2021_029
id	ascaad2021_029
authors	Goubran, Sherif; Carmela Cucuzzella, Mohamed Ouf
year	2021
title	Eco-Nudging: Interactive Digital Design to Solicit Immediate Energy Actions in The Built Space
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 177-189
summary	In the built space, building occupants, their behaviours and control actions are research areas that have gained a lot of attention. This is well justified since energy behaviours can result in differences of up to 25% in building energy consumption. Previous research recommends exploring ways to influence occupants' energy behaviour – through eco-feedback and by directly engaging occupants with building controls. Very little attention has been given to the role digital art and design can play in soliciting and changing human energy-related actions and behaviours in the built space. This paper proposes a new process that combines eco-feedback, gamification, and ecological digital art to trigger occupants to take immediate and precise control actions in the built space. We design, deploy and test this by creating an immersive human-building-interaction apparatus, which we place in a month-long exhibition. This experimental interface was informed by a novel vision for engagement-based human-building interactions deeply rooted in aesthetics, digital art and design. It also uses digital art to mediate between the occupants and energy-performance of spaces by redefining their relationship with and perception of energy – moving from metrics and quantities understanding to one that is art and emotion-based. The analysis reveals that this new type of human-engagement-based interactive building-control mechanism can add a significant layer of influence on energy-related actions – without revoking the individuals' ability to control their environment. It also highlights digital design and art's power in guiding actions and interactions with the built space.
series	ASCAAD
email
last changed	2021/08/09 13:11

_id	acadia21_92
id	acadia21_92
authors	Imai, Nate; Conway, Matthew
year	2021
title	Data Waltz
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 92-99.
doi	https://doi.org/10.52842/conf.acadia.2021.092
summary	This paper explores the impacts of the Internet of Things (IoT) on the field of interactive architecture and the ways this novel technology enables realignments toward inclusive and critical practices in the design of computational systems across different scales. Specifically, it examines how the integration of IoT in the design of architectural surfaces can encourage interaction between local and remote users and increase accessibility amongst contributors. Beginning with a survey of media facades and the superimposition of architectural surfaces with projected images, the paper outlines a historical relationship between buildings and the public realm through advancements in technology. The paper next reveals ways in which IoT can transform the field of interactive architecture through the documentation and analysis of a project that stages an encounter between local and remote Wikipedia contributors. The installation creates a feedback loop for engaging Wikipedia in real-time, allowing visitors to follow and produce content from their interactions with the gallery’s physical environment. Light, sound, and fabric contextualize the direction and volume of real-time user-generated event data in relation to the gallery’s location, creating an interface that allows participants to dance with dynamic bodies of knowledge. By incorporating IoT with the field of interactive architecture, this project creates a framework for designing computational systems responsive to multiple scales and expanding our understanding of computational publics.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2021_127
id	caadria2021_127
authors	Lin, Chaohe and Lo, Tian Tian
year	2021
title	Expanding the Methods of Human-VR Interaction (HVRI) for Architectural Design Process
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. 173-182
doi	https://doi.org/10.52842/conf.caadria.2021.2.173
summary	The emergence of virtual reality technology now brings the possibility of new design methods. Virtual reality technology allows architects to feel space better and express design ideas more intuitively. With the interactive perception equipment and VR glasses, geometric shapes can be created and modified in a virtual environment, replacing the mouse and keyboard to complete the creation of space in the early stage of the design process. At present, the application of virtual reality in the architectural design process has some problems include unnatural interaction, low accuracy, high work cost. This paper will summarize the interactive methods of virtual reality technology in various current cases and compare the input and output of the device by analyzing the matrix method. We can explore interactions that are beneficial to architectural design. Using these interactive methods, we can expand the interface relationship between humans and the virtual environment.
keywords	HCI; HVRI; Interaction; Digital Architecture Design; Virtual Reality
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2023_187
id	caadria2023_187
authors	Lopez Rodriguez, Alvaro and Pantic, Igor
year	2023
title	Augmented Environments: The Architecture for the Augmented Era
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 403–412
doi	https://doi.org/10.52842/conf.caadria.2023.1.403
summary	Human imagination has played with the idea of an alternative technological world for years. From dystopian proposals like Neuromancer or The Matrix to more positive views like the recent Upload series, the exploration of the friction between the digital world and the physical world has entertained the imagination of our society for decades. Outside the fictional environments, the omnipresence of the internet and the development of “the cloud” are showing that the virtual world is possible and that the idea of a Metaverse is no longer part of science fiction but a very real future for human relations (Winters 2021). In line with the idea of the Metaverse, the intersection of the virtual and the physical world is being explored through the idea of Extended Realities. Technology is allowing humans to enhance their capabilities more than ever, and in fact, it has been proposed that we are entering the Augmented era (King 2014). This paper explores the opportunities and possible challenges that “Extended Architecture” has by analyzing a research project based on augmented reality as the media to explore these ideas. This project will propose a speculative approach to how the fact that in the recent future, everyone will have access to an AR device will change the way we perceive and understand our architectural environment.
keywords	Work in progress, Virtual and Augmented Environments, Disruptive Modes of Practice and Pedagogy, Extended Realities, Machine Learning
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	acadia21_48
id	acadia21_48
authors	Nahmad Vazquez, Alicia; Chen, Li
year	2021
title	Automated Generation of Custom Fit PPE Inserts
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 48-57.
doi	https://doi.org/10.52842/conf.acadia.2021.048
summary	This research presents a machine learning-based interactive design method for the creation of customized inserts that improve the fit of the PPE 3M 1863 and 3M 8833 respiratory face masks. These two models are the most commonly used by doctors and professionals during the recent covid19 pandemic. The proper fit of the mask is crucial for their performance. Characteristics and fit of current leading market brands were analyzed to develop a parametric design software workflow that results in a 3D printed insert customized to specific facial features and the mask that will be used. The insert provides a perfect fit for the respirator mask. Statistical face meshes were generated from an anthropometric database, and 3D facial scans and photos were taken from 200 doctors and nurses on an NHS trust hospital. The software workflow can start from either a 2D image of the face (picture) or a 3D mesh taken from a scanning device. The platform uses machine learning and a parametric design workflow based on key performance facial parameters to output the insert between the face and the 3M masks. It also generates the 3d printing file, which can be processed onsite at the hospital. The 2D image approach and the 3D scan approach initializing the system were digitally compared, and the resultant inserts were physically tested by 20 frontline personnel in an NHS trust hospital. Finally, we demonstrate the criticality of proper fit on masks for doctors and nurses and the versatility of our approach augmenting an already tested product through customized digital design and fabrication.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia21_142
id	acadia21_142
authors	Quinteros, Cami; Rossi, Gabriella; Shawqy, Hesham; Papdopoulou, Iliana; Leon, David
year	2021
title	Imaginary Vessels
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 142-151.
doi	https://doi.org/10.52842/conf.acadia.2021.142
summary	Clay is one of the foundational materials in art and architecture, traced in the development of mud walls and the adobe module, and showcased in utilitarian and ornamental pottery. Wheel throwing is the process of shaping clay mainly into symmetrical objects, a complex craft in which the master potter has the knowledge and skill to manipulate the clay into the final design of various physical objects. This project explores how Machine Learning can be used to translate the richness and complexity of wheel throwing for digital fabrication. In this paper we present a surrogate digital dataset for robotic fabrication and geometric prediction used to train neural networks and provide a bridge between digital fabrication and handcraft. We report on the parametric model which abstracts wheel throwing as the interaction between a rotating mass and a given set of forces, as well as on data wrangling methods, dataset composition considerations, and training methodology. We present two models, one in which geometry is predicted based on a given set of forces, and a second in which forces are predicted based on a given geometry. Lastly, we give a critical assessment of the predictions of both networks and discuss future steps.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	cdrf2021_263
id	cdrf2021_263
authors	Risu Na and Haocheng Dai
year	2021
title	A Framework for Cypher-Physical Human-robot Collaborative Immersive MR Interaction – Beaux Arts Ball 4.0
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_25
summary	In this paper, we presented a human-robot collaborative mixed reality application – Beaux Arts Ball 4.0, in which a real-time interactive hybrid and physical architectural environment were designed and experienced through the tools and techniques of mixed reality, cypher-physical, teleoperation, telepresence, and automation. The application engaged the user and observer in a continuous loop of architectural transformation during the experience, where every type of sensory was blurred between physical and digital perception.
series	cdrf
email
last changed	2022/09/29 07:53

_id	acadia21_76
id	acadia21_76
authors	Smith, Rebecca
year	2021
title	Passive Listening and Evidence Collection
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 76-81.
doi	https://doi.org/10.52842/conf.acadia.2021.076
summary	In this paper, I present the commercial, urban-scale gunshot detection system ShotSpotter in contrast with a range of ecological sensing examples which monitor animal vocalizations. Gunshot detection sensors are used to alert law enforcement that a gunshot has occurred and to collect evidence. They are intertwined with processes of criminalization, in which the individual, rather than the collective, is targeted for punishment. Ecological sensors are used as a “passive” practice of information gathering which seeks to understand the health of a given ecosystem through monitoring population demographics, and to document the collective harms of anthropogenic change (Stowell and Sueur 2020). In both examples, the ability of sensing infrastructures to “join up and speed up” (Gabrys 2019, 1) is increasing with the use of machine learning to identify patterns and objects: a new form of expertise through which the differential agendas of these systems are implemented and made visible. I trace the differential agendas of these systems as they manifest through varied components: the spatial distribution of hardware in the existing urban environment and / or landscape; the software and other informational processes that organize and translate the data; the visualization of acoustical sensing data; the commercial factors surrounding the production of material components; and the apps, platforms, and other forms of media through which information is made available to different stakeholders. I take an interpretive and qualitative approach to the analysis of these systems as cultural artifacts (Winner 1980), to demonstrate how the political and social stakes of the technology are embedded throughout them.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2021_285
id	ecaade2021_285
authors	Vaez Afshar, Sepehr, Eshaghi, Sarvin, Varinlioglu, Guzden and Balaban, Özgün
year	2021
title	Evaluation of Learning Rate in a Serious Game - Based on Anatolian cultural heritage
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 273-280
doi	https://doi.org/10.52842/conf.ecaade.2021.2.273
summary	Cultural heritage conservation has two aspects, tangible and intangible, both of which contribute greatly to the understanding of ancient inheritances. Due to the role of education in the preservation process, and the strength of the new media in the current era, serious games can play a key role in conservancy by transmitting the target culture. There is a gap in the serious game field in relation to Turkey's cultural heritage on the Silk Roads, underlining the motivation of this research. Hence, this study proposes the Anatolian Journey serious game, which is developed in the Twine platform, designed to transmit Turkey's tangible and intangible cultural heritage, providing comprehensive information on the Seljuk caravanserais, located on the Silk Roads. Moreover, the research compares undergraduate and graduate students' gains in knowledge of heritage data while playing a serious game and encountering the same content in text form with an online survey.
keywords	Digital Heritage; Serious Game; The Silk Roads; Anatolian Caravanserais; Learning Rate
series	eCAADe
email
last changed	2022/06/07 07:57

_id	cdrf2021_242
id	cdrf2021_242
authors	Waishan Qiu , Wenjing Li, Xun Liu, and Xiaokai Huang
year	2021
title	Subjectively Measured Streetscape Qualities for Shanghai with Large-Scale Application of Computer Vision and Machine Learning
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_23
summary	Recently, many new studies emerged to apply computer vision (CV) to street view imagery (SVI) dataset to objectively extract the view indices of various streetscape features such as trees to proxy urban scene qualities. However, human perceptions (e.g., imageability) have a subtle relationship to visual elements which cannot be fully captured using view indices. Conversely, subjective measures using survey and interview data explain more human behaviors. However, the effectiveness of integrating subjective measures with SVI dataset has been less discussed. To address this, we integrated crowdsourcing, CV, and machine learning (ML) to subjectively measure four important perceptions suggested by classical urban design theory. We first collected experts’ rating on sample SVIs regarding the four qualities which became the training labels. CV segmentation was applied to SVI samples extracting streetscape view indices as the explanatory variables. We then trained ML models and achieved high accuracy in predicting the scores. We found a strong correlation between predicted complexity score and the density of urban amenities and services Point of Interests (POI), which validates the effectiveness of subjective measures. In addition, to test the generalizability of the proposed framework as well as to inform urban renewal strategies, we compared the measured qualities in Pudong to other five renowned urban cores worldwide. Rather than predicting perceptual scores directly from generic image features using convolution neural network, our approach follows what urban design theory suggested and confirms various streetscape features affecting multi-dimensional human perceptions. Therefore, its result provides more interpretable and actionable implications for policymakers and city planners.
series	cdrf
last changed	2022/09/29 07:53

_id	ecaade2021_247
id	ecaade2021_247
authors	Wibranek, Bastian, Liu, Yuxi, Funk, Niklas, Belousov, Boris, Peters, Jan and Tessmann, Oliver
year	2021
title	Reinforcement Learning for Sequential Assembly of SL-Blocks - Self-interlocking combinatorial design based on Machine Learning
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 1, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 27-36
doi	https://doi.org/10.52842/conf.ecaade.2021.1.027
summary	Adaptive reconfigurable structures are seen as the next big step in the evolution of architecture. However, to achieve this vision, new tools are required that enable autonomous configuration of given elements based on a specified design objective. Various approaches have been considered in the past, ranging from rule-based methods to evolutionary optimization. Although successful in applications where search heuristics or informative objective functions can be provided, these methods struggle with long-term planning problems. In this paper, we tackle the problem of sequential assembly of SL-blocks which has the character of a combinatorial optimization problem. We explore the applicability of deep reinforcement learning algorithms that recently showed great success on combinatorial problems in other domains, such as board games and molecular design. We highlight the unique challenges presented by the architectural design setting and compare the performance to evolutionary computation and heuristic search baselines.
keywords	Reinforcement Learning; Architectural Assembly; Discrete Design; SL-blocks; Dry Joined
series	eCAADe
email
last changed	2022/06/07 07:57

_id	cdrf2021_35
id	cdrf2021_35
authors	Yubo Liu, Chenrong Fang, Zhe Yang, Xuexin Wang, Zhuohong Zhou, Qiaoming Deng, and Lingyu Liang
year	2021
title	Exploration on Machine Learning Layout Generation of Chinese Private Garden in Southern Yangtze
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_4
summary	Machine learning has been proved to be feasible and reasonable in architectural field by extensive researches recently, whereas its potential is far from being tapped. Previous studies show that the training of GAN by labelling can enable a computer to grasp interrelationship of spatial elements and logical relationship between spatial elements and boundary. This study set the learning object as layout of private gardens in southern Yangtze with higher complexity. Chinese scholars usually analyse private garden layout based on their observation and experience. In this paper, based on Pix2Pix model, we enable a computer to generate private garden layout plan for given site conditions by learning classic cases of traditional Chinese private gardens. Through the experiment, taking Lingering garden as example, we continuously adjust the labelling method to improve learning effect. The finally trained model can quickly generate private garden layout and aid designers to complete scheme design with private garden element corpus. In addition, the working process of training GAN enables us to discover and verify some private garden layout rules that have not been paid attention to.
series	cdrf
email
last changed	2022/09/29 07:53

_id	caadria2021_000
id	caadria2021_000
authors	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.)
year	2021
title	CAADRIA 2021: Projections, Volume 1
source	PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, 768 p.
doi	https://doi.org/10.52842/conf.caadria.2021.1
summary	Rapidly evolving technologies are increasingly shaping our societies as well as our understanding of the discipline of architecture. Computational developments in fields such as machine learning and data mining enable the creation of learning networks that involve architects alongside algorithms in developing new understanding. Such networks are increasingly able to observe current social conditions, plan, decide, act on changing scenarios, learn from the consequences of their actions, and recognize patterns out of complex activity networks. While digital technologies have already enabled architecture to transcend static physical boxes, new challenges of the present and visions for the future continue to call for both innovative responses integrating emerging technologies into experimental architectural practice and their critical reflection. In this process, the capability of adapting to complex social and environmental challenges through learning, prototyping and verifying solution proposals in the context of rapidly shifting realities has become a core challenge to the architecture discipline. Supported by advancing technologies, architects and researchers are creating new frameworks for digital workflows that engage with new challenges in a variety of ways. Learning networks that recognize patterns from massive data, rapid prototyping systems that flexibly iterate innovative physical solutions, and adaptive design methods all contribute to a flexible and networked digital architecture that is able to learn from both past and present to evolve towards a promising vision of the future.
series	CAADRIA
last changed	2022/06/07 07:49

_id	caadria2021_001
id	caadria2021_001
authors	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.)
year	2021
title	CAADRIA 2021: Projections, Volume 2
source	PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, 764 p.
doi	https://doi.org/10.52842/conf.caadria.2021.2
summary	Rapidly evolving technologies are increasingly shaping our societies as well as our understanding of the discipline of architecture. Computational developments in fields such as machine learning and data mining enable the creation of learning networks that involve architects alongside algorithms in developing new understanding. Such networks are increasingly able to observe current social conditions, plan, decide, act on changing scenarios, learn from the consequences of their actions, and recognize patterns out of complex activity networks. While digital technologies have already enabled architecture to transcend static physical boxes, new challenges of the present and visions for the future continue to call for both innovative responses integrating emerging technologies into experimental architectural practice and their critical reflection. In this process, the capability of adapting to complex social and environmental challenges through learning, prototyping and verifying solution proposals in the context of rapidly shifting realities has become a core challenge to the architecture discipline. Supported by advancing technologies, architects and researchers are creating new frameworks for digital workflows that engage with new challenges in a variety of ways. Learning networks that recognize patterns from massive data, rapid prototyping systems that flexibly iterate innovative physical solutions, and adaptive design methods all contribute to a flexible and networked digital architecture that is able to learn from both past and present to evolve towards a promising vision of the future.
series	CAADRIA
last changed	2022/06/07 07:49

_id	ascaad2021_021
id	ascaad2021_021
authors	Albassel, Mohamed; Mustafa Waly
year	2021
title	Applying Machine Learning to Enhance the Implementation of Egyptian Fire and Life Safety Code in Mega Projects
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 7-22
summary	Machine Learning has become a significant research area in architecture; it can be used to retrieve valuable information for available data used to predict future instances. the purpose of this research was to develop an automated workflow to enhance the implementation of The Egyptian fire & life safety (FLS) code in mega projects and reduce the time wasted on the traditional process of rooms’ uses, occupant load, and egress capacity calculations to increase productivity by applying Supervised Machine Learning based on classification techniques through data mining and building datasets from previous projects, and explore the methods of preparation and analyzing data (text cleanup- tokenization- filtering- stemming-labeling). Then, provide an algorithm for classification rules using C# and python in integration with BIM tools such as Revit-Dynamo to calculate cumulative occupant load based on factors which are mentioned in the Egyptian FLS code, determine classification and uses of rooms to validate all data related to FLS. Moreover, calculating the egress capacity of means of egress for not only exit doors but also exit stairs. In addition, the research is to identify a clear understanding about ML and BIM through project case studies and how to build a model with the needed accuracy.
series	ASCAAD
email
last changed	2021/08/09 13:11

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