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 1866

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

_id	1d2b
authors	Minsky, M.
year	1963
title	Steps toward artificial intelligence
source	E.A. Feigenbaum & J. Feldman, eds., Computers and Thought (McGraw-Hill, New York) 406-450.
summary	The problems of heuristic programming-of making computers solve really difficult problems-are divided into five main areas: Search, Pattern-Recognition, Learning, Planning, and Induction. Wherever appropriate, the discussion is supported by extensive citation of the literature and by descriptions of a few of the most successful heuristic (problem-solving) programs constructed to date. The adjective "heuristic," as used here and widely in the literature, means related to improving problem-solving performance; as a noun it is also used in regard to any method or trick used to improve the efficiency of a problem-solving system. A "heuristic program," to be considered successful, must work well on a variety of problems, and may often be excused if it fails on some. We often find it worthwhile to introduce a heuristic method, which happens to cause occasional failures, if there is an over-all improvement in performance. But imperfect methods are not necessarily heuristic, nor vice versa. Hence "heuristic" should not be regarded as opposite to "foolproof"; this has caused some confusion in the literature.
series	other
email
last changed	2003/04/23 15:50

_id	sigradi2013_243
id	sigradi2013_243
authors	Andia, Alfredo
year	2013
title	Automated Architecture: Why CAD, Parametrics and Fabrication are Really old News
source	SIGraDi 2013 [Proceedings of the 17th Conference of the Iberoamerican Society of Digital Graphics - ISBN: 978-956-7051-86-1] Chile - Valparaíso 20 - 22 November 2013, pp. 83 - 87
summary	Automation is transforming a significant number of industries today. This paper discusses how the Design and Construction industry is also entering into a new era of automation. In the paper I observe that designers are automating by using parametric tools (BIM, scripting, etc.) while contractors are moving into pre-fabrication and modularization. Both conceptualizations are incomplete. The paper presents how we are in the first steps of creating learning algorithms that develop specific intelligence in design synthesis and how the design field will became even more sophisticated as a second generation of multi-material 3D printing techniques produce new materials.
keywords	Automation; Architectural design; Artificial intelligence; Learning algorithms; Multi-material printers
series	SIGRADI
email
last changed	2016/03/10 09:47

_id	ecaade2023_328
id	ecaade2023_328
authors	Andreou, Alexis, Kontovourkis, Odysseas, Solomou, Solon and Savvides, Andreas
year	2023
title	Rethinking Architectural Design Process using Integrated Parametric Design and Machine Learning Principles
doi	https://doi.org/10.52842/conf.ecaade.2023.2.461
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 461–470
summary	Artificial Intelligence (AI) has the potential to process vast amounts of subjective and conflicting information in architecture. However, it has mostly been used as a tool for managing information rather than as a means of enhancing the creative design process. This work proposes an innovative way to enhance the architectural design process by incorporating Machine Learning (ML), a type of Artificial Intelligence (AI), into a parametric architectural design process. ML would act as a mediator between the architects' inputs and the end-users' needs. The objective of this work is to explore how Machine Learning (ML) can be utilized to visualize creative designs by transforming information from one form to another - for instance, from text to image or image to 3D architectural shapes. Additionally, the aim is to develop a process that can generate comprehensive conceptual shapes through a request in the form of an image and/or text. The suggested method essentially involves the following steps: Model creation, Revisualization, Performance evaluation. By utilizing this process, end-users can participate in the design process without negatively affecting the quality of the final product. However, the focus of this approach is not to create a final, fully-realized product, but rather to utilize abstraction and processing to generate a more understandable outcome. In the future, the algorithm will be improved and customized to produce more relevant and specific results, depending on the preferences of end-users and the input of architects.
keywords	End-users, Architects, Mass personalization, Visual programming, Neural Network Algorithm
series	eCAADe
email
last changed	2023/12/10 10:49

_id	caadria2022_208
id	caadria2022_208
authors	Bielski, Jessica, Langenhan, Christoph, Ziegler, Christoph, Eisenstadt, Viktor, Petzold, Frank, Dengel, Andreas and Althoff, Klaus-Dieter
year	2022
title	The What, Why, What-If and How-To for Designing Architecture, Explainability for Auto-Completion of Computer-Aided Architectural Design of Floor Plan Layouting During the Early Design Stages
doi	https://doi.org/10.52842/conf.caadria.2022.2.435
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 435-444
summary	In the next thirty years, the world's population is expected to increase to ten billion people, posing major challenges for the construction industry. To meet the growing demands for residential housing in the future, architects need to work faster, more efficiently, and more sustainably, while increasing architectural quality. The hypothetical intelligent design assistant WHITE BRIDGE, based on the methods of the 'metis' projects, suggests further design steps to support the architectural design decision-making processes of the early design phases. This facilitates faster and better decisions early in the process for a more responsible resource consumption, better mental well-being, and ultimately economic growth. Through a case study we investigate if additional information supports the understanding of these suggestions to reduce the cognitive workload of architectural design decisions on the backdrop of their respective representation. The paper contributes an approach for visualising explanations of an intelligent design assistant, their integration into paper prototypes for case studies, and a workflow for data collection and analysis. The results suggest that the cognitive horizon of the architects is broadened by the explanations, while the visualisation methods significantly influence the usefulness and use of the conveyed information within the explanations.
keywords	Explainability, Artificial intelligence, XAI, SDG 3, SDG 8, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2024_302
id	ecaade2024_302
authors	Bielski, Jessica; Karaali, Ozan; Eisenstadt, Viktor; Langenhan, Christoph; Petzold, Frank
year	2024
title	Sequencing the Architectural Design Process for Artificial Intelligence - A design-theory-based framework for machine learning approaches
doi	https://doi.org/10.52842/conf.ecaade.2024.1.449
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 1, pp. 449–458
summary	Similar process models of the architectural design process of the early design stages have been formalised. However, recognition by machine learning (ML) based approaches fails due to the individuality and vagueness of the inherent method of sketching. Nevertheless, contemporary ML approaches have the potential to support the architectural design process through auto-completion-based suggestions. In order to provide data for ML-based suggestion generation, we propose a customisable framework with according steps. Drawing from design theory, it is establishes the design process as sequences of three levels of detail and their respective linking. These literature-based sequences serve to label sketch protocol studies. Finally, the framework is validated through Recurrent Neural Networks (RNNs) with Long-Short-Term-Memory (LSTM) architecture trained in isolation on sequences of different level of detail, for prediction purposes.
keywords	Design theory, Architectural design process, Design process, Sequencing, Data preparation, Artificial intelligence, Machine learning
series	eCAADe
email
last changed	2024/11/17 22:05

_id	5dff
authors	Bricken, M.
year	1994
title	Virtual Worlds: No Interface to Design
source	Cyberspace - First Steps, M.Benedikt ed, MIT Press
summary	In a virtual world, we are inside an environment of pure information that we can see, hear, and touch. The technology itself is invisible, and carefully adapted to human activity so that we can behave naturally in this artificial world. We can create any imaginable environment and we can experience entirely new perspectives and capabilities within it. A virtual world can be informative, useful, and fun; it can also be boring and uncomfortable. The difference is in the design. The platform and the interactive devices we use, the software tools and the purpose of the environment are all elements in the design of virtual worlds. But the most important component in designing comfortable, functional worlds is the person inside them. Cyberspace technology couples the functions of the computer with human capabilities. This requires that we tailor the technology to people, and refine the fit to individuals. We then have customized interaction with personalized forms of information that can amplify our individual intelligence and broaden our experience. Designing virtual worlds is a challenging departure from traditional interface design. In the first section of this chapter I differentiate between paradigms for screen-based interface design and paradigms for creating virtual worlds. The engineer, the designer, and the participant co-create cyberspace. Each role carries its own set of goals and expectations, its own model of the technology's salient features. In the second section of the chapter I address these multiple perspectives, and how they interrelate in the cooperative design process. In conclusion, I consider broader design issues, including control, politics, and emergent phenomena in cyberspace.
series	other
last changed	2003/11/21 15:16

_id	00bc
authors	Chen, Chen-Cheng
year	1991
title	Analogical and inductive reasoning in architectural design computation
source	Swiss Federal Institute of Technology, ETH Zurich
summary	Computer-aided architectural design technology is now a crucial tool of modern architecture, from the viewpoint of higher productivity and better products. As technologies advance, the amount of information and knowledge that designers can apply to a project is constantly increasing. This requires development of more advanced knowledge acquisition technology to achieve higher functionality, flexibility, and efficient performance of the knowledge-based design systems in architecture. Human designers do not solve design problems from scratch, they utilize previous problem solving episodes for similar design problems as a basis for developmental decision making. This observation leads to the starting point of this research: First, we can utilize past experience to solve a new problem by detecting the similarities between the past problem and the new problem. Second, we can identify constraints and general rules implied by those similarities and the similar parts of similar situations. That is, by applying analogical and inductive reasoning we can advance the problem solving process.The main objective of this research is to establish the theory that (1) design process can be viewed as a learning process, (2) design innovation involves analogical and inductive reasoning, and (3) learning from a designer's previous design cases is necessary for the development of the next generation in a knowledge-based design system. This thesis draws upon results from several disciplines, including knowledge representation and machine learning in artificial intelligence, and knowledge acquisition in knowledge engineering, to investigate a potential design environment for future developments in computer-aided architectural design. This thesis contains three parts which correspond to the different steps of this research. Part I, discusses three different ways - problem solving, learning and creativity - of generating new thoughts based on old ones. In Part II, the problem statement of the thesis is made and a conceptual model of analogical and inductive reasoning in design is proposed. In Part III, three different methods of building design systems for solving an architectural design problem are compared rule-based, example-based, and case-based. Finally, conclusions are made based on the current implementation of the work, and possible future extensions of this research are described. It reveals new approaches for knowledge acquisition, machine learning, and knowledge-based design systems in architecture.
series	thesis:PhD
email
last changed	2003/05/10 05:42

_id	ecaade2022_65
id	ecaade2022_65
authors	Halici, Süheyla Müge and Gül, Leman Figen
year	2022
title	Utilizing Generative Adversarial Networks for Augmenting Architectural Massing Studies: AI-assisted Mixed Reality
doi	https://doi.org/10.52842/conf.ecaade.2022.1.323
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 323–330
summary	A technique for architectural massing studies in Mixed Reality (MR) is described. Generative Adversarial Networks let an object appear to have a different material than it actually has. The benefits during design are twofold. From one side the congruence between shape and material are subject to verification in real-time. From the other side, the designer is liberated from the usual restrictions and biases as to shape that are inevitable due to the mechanical properties of a mock-up. This is referred to as artificial intelligence assisted MR (AI-A MR) in this work. The technique consists of two steps: based on preparing synthetic data in Rhino/Grasshopper to be trained with an image-to- image translation model and implemented to the trained model in MR design environment. Next to the practical merits, a contribution of the work with respect to MR methodology is that it exemplifies the solution of some persistent tracking and registration problems.
keywords	Hybrid Design Environment, Dynamic Design Models, Mixed Reality, Generative Adversarial Networks, Image-to-Image Translation, Tracking
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_231
id	caadria2022_231
authors	Kim, Frederick Chando and Huang, Jeffrey
year	2022
title	Deep Architectural Archiving (DAA), Towards a Machine Understanding of Architectural Form
doi	https://doi.org/10.52842/conf.caadria.2022.1.727
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 727-736
summary	With the ‚digital turn‚, machines now have the intrinsic capacity to learn from big data in order to understand the intricacies of architectural form. This paper explores the research question: how can architectural form become machine computable? The research objective is to develop "Deep Architectural Archiving‚ (DAA), a new method devised to address this question. DAA consists of the combination of four distinct steps: (1) Data mining, (2) 3D Point cloud extraction, (3) Deep form learning, as well as (4) Form mapping and clustering. The paper discusses the DAA method using an extensive dataset of architecture competitions in Switzerland (with over 360+ architectural projects) as a case study resource. Machines learn the particularities of forms using 'architectural' point clouds as an opportune machine-learnable format. The result of this procedure is a multidimensional, spatialized, and machine-enabled clustering of forms that allows for the visualization of comparative relationships among form-correlated datasets that exceeds what the human eye can generally perceive. Such work is necessary to create a dedicated digital archive for enhancing the formal knowledge of architecture and enabling a better understanding of innovation, both of which provide architects a basis for developing effective architectural form in a post-carbon world.
keywords	artificial intelligence, deep learning, architectural form, architectural competitions, architectural archive, 3D dataset, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	6045
authors	Rychener, Michael D.
year	1984
title	Expert systems for Engineering Design : Problem Components, Technique, & Prototypes
source	31 p. : charts Design Research Center, CMU, March, 1984. DRC-0502-83. includes bibliography
summary	A number of problems in diagnosis and engineering design can be solved by using current expert system techniques. This paper enumerates the main components of such problems and the steps that are taken in solving them. A few prototypical artificial intelligence systems embody techniques that can be applied to engineering problems are surveyed, and their relevance to components of design problems is discussed. Some expert system in design domain are summarized, with emphasis on aspects that can illustrate wider applicability of the techniques
keywords	expert systems, AI, problem solving, design, methods, engineering
series	CADline
last changed	2003/06/02 13:58

_id	ecaade2023_57
id	ecaade2023_57
authors	Taºdelen, Merve, Güleç Özer, Derya and Akçay Kavakoglu, Ayºegül
year	2023
title	The Quest of Spatial Presence by Puzzle-Solving Games in VR
doi	https://doi.org/10.52842/conf.ecaade.2023.2.833
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 833–842
summary	The experience of artificial objects in the virtual environment and the illusion of being there is a primary affordance of the virtual reality (VR) environment. The conviction of being located in a mediated environment is referred to as spatial presence. Although some studies investigate the relationship between VR and spatial intelligence, how users build a spatial presence in VR game environments remains ambiguous. Regarding that, this study tries to elaborate on the spatial presence experience construction and its characteristics in virtual reality (VR) puzzle-solving games by revealing the relationships between game mechanics and spatial presence notion. In this study, the presence-spatial performance relations are initially investigated based on previous works and analyzed in terms of spatial definition. Suppose the VR task performance depends on spatial abilities, people with higher spatial ability finish tasks faster, and their spatial presence score will be higher than people with lower spatial ability. A VR game called Golden Gate VR will be used as a case study to test and elaborate on the hypothesis above. This ongoing study has five steps: (1) Development of the game environment, (2) pre-psychometric assessment for visuo-spatial ability (Pre-Test), (3) Experience of the VR Game, (4) Evaluation of the experiences, (5) Re-development of the game environment. Experiences of the players’ will be evaluated in terms of Mental Imagery, Mental Rotation and Spatial Orientation regarding Spatial Presence Experience Scale (SPES). The first four steps will be elaborated on in this paper.
keywords	immersive virtual reality, spatial presence, spatial ability, puzzle-solving game
series	eCAADe
email
last changed	2023/12/10 10:49

_id	sigradi2021_166
id	sigradi2021_166
authors	Vivanco, Tomas, Valencia, Antonia and Yuan, Philip
year	2021
title	Methodological Implementation of Stylegans Algorithms and Its Change of Paradigm in the Education, Practice and Role of Designers
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. 55–66
summary	The integration of Artificial Intelligence algorithms into computational design processes promote a human-machine collaboration, transforming the role of conventional designers into meta-designer as a product of this collaboration. Specifically, StyleGAN's algorithms offer a novel approach to experimenting with shapes from previously designed images of products or objects. This article presents the application of a methodology for image experimentation to designers without previous knowledge of computation and programming. Each of the steps was developed through different cases for different speculative object production, using artificial intelligence algorithms, and reflecting - in an applied way - the designer's role as curator and co- creator of the creative process in conjunction with computing.
keywords	Stylegan, design methods, design education, artificial intelligence.
series	SIGraDi
email
last changed	2022/05/23 12:10

_id	ecaade2024_60
id	ecaade2024_60
authors	Wan, Zijun; Sun, Shuaibing; Meng, Fanjing; Yan, Yu
year	2024
title	How Augment Reality Support Public Participation in the Urban Design Decision-Making: A ten - year literature review
doi	https://doi.org/10.52842/conf.ecaade.2024.2.455
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 455–464
summary	Emerging applications of AR have demonstrated its powerful visualization capabilities, which is a potential solution to enhance public participation in the urban design process. However, there is still a lack of complete understanding of how AR gets involved in this decision-making process. Therefore, this paper reviews 33 empirical studies relating to the topic through the four steps of “PRISMA”. The results indicate that the quantity and quality of research is increasing yearly. As AR technology progresses, the techniques and research methods used in those studies show a trend toward diversification and customization; this has also led to a shift in the scale of urban design from large and abstract to small and concrete. In terms of content, the topics have gradually changed from “people group” to “technology”, and then to “environment”. Notably, a small number of cases in tangible interaction and multi-user collaboration have emerged from 2020 — areas showing great promise. In terms of user assessments, most studies give positive feedback, but there are currently concerns about problems in poor AR visualizations, privacy risks, and the social inequality caused by technical affordance.
keywords	Augment reality, Urban design and planning, Public participation, Collaborative and participative design, Design decision-making
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ascaad2022_024
id	ascaad2022_024
authors	Yonder, Veli
year	2022
title	Using Artificial Neural Networks and Space Syntax Techniques to Understand Mass Housing Design Parameters
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 283-299
summary	The design of mass housing is a complex process that involves the use of a large number of components and parameters. The field of design has unavoidably been changed by the impact of digitalization, which has resulted in the proliferation of computational design models, data structures, artificial intelligence, and an algorithmic way of thinking. Artificial neural networks, space syntax methodologies, predefined rules will help shape the steps of the schematic design process and establish certain limitations. Within the confines of this research, predefined guidelines were used to bring about geometric variances in the design of mass houses. Both traditional and digital instruments were utilized in the process. Methodologies based on artificial neural network models and space syntax techniques were utilized to investigate case studies and develop prototypes. The artificial neural network model is designed to understand the factors affecting mass housing design parameters. The importance percentages of the parameters were determined according to the outputs of this model. Besides, methodologies based on space syntax have had a significant impact, both on decision-making processes and on feedback-based design. In this study, several digital tools were used to analyze such as visibility graph analyzes, node-based techniques, and isovist analysis. In the section devoted to the conclusion, the comparison of the various prototypes that were obtained, the findings of the space syntax analysis, and the various stages of model development are discussed.
series	ASCAAD
email
last changed	2024/02/16 13:24

_id	caadria2003_c2-4
id	caadria2003_c2-4
authors	Al-Sallal, Khaled A.
year	2003
title	Integrating Energy Design Into Caad Tools: Theoretical Limits and Potentials
doi	https://doi.org/10.52842/conf.caadria.2003.323
source	CAADRIA 2003 [Proceedings of the 8th International Conference on Computer Aided Architectural Design Research in Asia / ISBN 974-9584-13-9] Bangkok Thailand 18-20 October 2003, pp. 323-340
summary	The study is part of a research aims to establish theoretical grounds essential for the development of user efficient design tools for energy-conscious architectural design, based on theories in human factors of intelligent interfaces, problem solving, and architectural design. It starts by reviewing the shortcomings of the current energy design tools, from both architectural design and human factor points of view. It discusses the issues of energy integration with design from three different points of view: architectural, problem-solving, and human factors. It evaluates theoretically the potentials and limitations of the current approaches and technologies in artificial intelligence toward achieving the notion "integrating energy design knowledge into the design process" in practice and education based on research in the area of problem solving and human factors and usability concerns. The study considers the user interface model that is based on the cognitive approach and can be implemented by the hierarchical structure and the object-oriented model, as a promising direction for future development. That is because this model regards the user as the center of the design tool. However, there are still limitations that require extensive research in both theoretical and implementation directions. At the end, the study concludes by discussing the important points for future research.
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	acadia21_100
id	acadia21_100
authors	Ghandi, Mona; Ismail, Mohamed; Blaisdell, Marcus
year	2021
title	Parasympathy
doi	https://doi.org/10.52842/conf.acadia.2021.100
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. 100-109.
summary	Parasympathy is an interactive spatial experience operating as an extension of visitors’ minds. By integrating Artificial Intelligence (AI), wearable technologies, affective computing (Picard 1995; Picard 2003), and neuroscience, this project blurs the lines between the physical, digital, and biological spheres and empowers users’ brains to solicit positive changes from their spaces based on their real-time biophysical reactions and emotions. The objective is to deploy these technologies in support of the wellbeing of the community especially when related to social matters such as inclusion and social justice in our built environment. Consequently, this project places the users’ emotions at the very center of its space by performing real-time responses to the emotional state of the individuals within the space.
series	ACADIA
type	project
email
last changed	2023/10/22 12:06

_id	acadia23_v2_72
id	acadia23_v2_72
authors	Hosmer, Tyson; Mutis, Sergio; Hughes, Eric; He, Ziming; Siedler, Philipp; Gheorghiu, Octavian; Erdinçer, Bariº
year	2023
title	Autonomous Collaborative: Robotic Reconfiguration with Deep Multi-Agent Reinforcement Learning (ACRR+DMARL)
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 72-90.
summary	To address the unprecedented challenges of the global climate and housing crises, requires a radical change in the way we conceive, plan, and construct buildings, from static continuous objects to adaptive eco-systems of reconfigurable parts. Living systems in nature demonstrate extraordinary scalable efficiencies in adaptive construction with simple flexible parts made from sustainable materials. The interdisciplinary field of collec- tive robotic construction (CRC) inspired by natural builders has begun to demonstrate potential for scalable, adaptive, resilient, and low-cost solutions for building construc- tion with simple robots. Yet, to explore the opportunities inspired by natural systems, CRC systems must be developed utilizing artificial intelligence for collaborative and adaptive construction, which has yet to be explored. Autonomous Collaborative Robotic Reconfiguration (ACRR) is a robotic material system with an adaptive lifecycle trained with deep, multi-agent reinforcement learning (DMARL) for collaborative reconfigura- tion. Autonomous Collaborative Robotic Reconfiguration is implemented through three interrelated components codesigned in relation to each other: 1) a reconfigurable robotic material system; 2) a cyber-physical simulation, sensing, and control system; and 3) a framework for collaborative robotic intelligence with DMARL. The integration of the CRC system with bidirectional cyber-physical control and collaborative intelligence enables ACRR to operate as a scalable and adaptive architectural eco-system. It has the potential not only to transform how we design and build architecture, but to fundamentally change our relationship to the built environment moving from automated toward autonomous construction.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	905d
authors	Maltret, J.-L. and Zoller, J.
year	1996
title	Simulation of architectural and urban morphology
source	OEEPE Workshop on 3D-city models, Bonn, October 1996.
summary	The Remus project aims at conceiving a simulation tool for both architectural and urban morphology, building a computer system using artificial intelligence tools, and computer graphics. Remus is made of a base of architectural knowledge, an expert system, and an interactive graphical environment for generating and displaying architectural objects. In this paper are presented new developments concerning evolution toward virtual reality models.
series	other
last changed	2003/04/23 15:50

_id	acadia21_564
id	acadia21_564
authors	Pellicano, Emily; Sturken, Carlo
year	2021
title	GPT-OA; Generative Pretrained Treatise--On Architecture
doi	https://doi.org/10.52842/conf.acadia.2021.564
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. 564-571.
summary	Technological advancements throughout the industrial era have created more efficient, more economical, and safer machines to aid – and often replace – human operations, continually altering our ways of knowledge and world making. Each industrial advancement radically changes social, political, economic, environmental, and even linguistic conditions. Currently upon us is artificial intelligence (AI); machine to human and machine to machine communications. Our investigation examines AI as a creative tool, instead of a machine for industry. Recent advancements in natural language processing have made artificially intelligent machines, specifi cally Generative Pretrained Transformers (GPT), a potential active partici- pant in a creative computational discourse. Our particular interest in GPT, and the core of this project, explores the role of language in machine learning and the role of the author and editor within a continually expanding network of agents in the construction of our collective environments.
series	ACADIA
type	field note
email
last changed	2023/10/22 12:06

_id	acadia17_482
id	acadia17_482
authors	Penman, Scott
year	2017
title	Toward Computational Play
doi	https://doi.org/10.52842/conf.acadia.2017.482
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 482- 491
summary	The day is not far off when autonomous, artificially intelligent agents will be employed in creative industries such as architecture and design. Artificial intelligence is rapidly becoming ubiquitous, and it has absorbed many capabilities once thought beyond its reach. As such, it is critical that we reflect on the relationship between AI and design. Design is often tasked with pushing the envelope in the quest for novel meaning and experience. Designers can’t always rely upon existing models to judge their work. Operating like this requires a curious and open mind, a willingness to eschew reward and occasionally break the rules, and a desire to explore for the sake of exploring. These behaviors fly in the face of traditional implementations of computation and raise difficult questions about the autonomy and subjectivity of artificially intelligent machines. This paper proposes computational play as a field of research that covers how and why designers roam as freely as they do, what the creative potential of such exploration might be, and how such techniques might responsibly be implemented in computational machines. The work argues that autotelism, defined as internal motivation, is an essential aspect of play and outlines how it can be incorporated in a computational framework. The work also demonstrates a proof-of-concept in the form of an autonomous drawing machine that is able to plot a drawing, view the drawing, and make decisions based on what it sees, bringing computational vision and computational drawing together into a cyclical process that permits the use of autotelic play behavior.
keywords	design methods; information processing; art and technology; computational / artistic cultures
series	ACADIA
email
last changed	2022/06/07 08:00

For more results click below: