Cellular Automata in High-Density Housing Design

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CELLULAR AUTOMATA A B O T T O M - UP A N A L Y S I S A N D D ES I GN T O O L F O R HI G H - D EN S I T Y A D A P T I V E H O U S I N G I N T HE D I GI T A L A G E.

INTRODUCTION This literature review is focused on the application of Cellular Automata (CA) as a generative tool in the design process of highdensity housing. The complexity of housing project is considerably similar with the complexity of CA, derived from the simple interaction between individual elements. This paper will briefly go through the history of CA in Architecture Design, the context of high-density housing, and the application of CA as an analysis and a design tool for housing project in the Digital Age. CELLULAR AUTOMATA Cellular Automata (CA) is “the computational method which can simulate process of growth of complex system generated by simple rules of relationship between each individual element” (Wolfram, 2002). The mathematical concept was first introduced in the 1940s by John von Neuman (1966) and developed by Ulam (1967), then gain popularity when Gardner (1970) presents John Conway’s “Game of Life” to popular culture in a form of 2D game generated grow patterns in 1970. Wolfram (2002) later formulated the CA concept to represent physical phenomena and its application in various fields of sciences.

Figure 1. Basic 3D Cellular Automata Terminology


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The use of CA in Architectural Design has been explored in research since the 1960s, from analyze the complexity of existing structure to generate organized patterns for new design in digital methods, and tend to suggest inspirational architectural forms (see for example Frazer, 1995). Cedric Price’s Generator Projects in 1978 could be considered as an early example for the use of CA in architecture. The project consisted of a kit of parts in a grid, which "enabled enclosures, gangways, screens, and services to be arranged and re-arranged to meet the changing requirements of the clients" (Hardingham, 2003). Frazer (1995), as one of the pioneer researcher in the architectural application of CA, experimented with a self-replicating CA model in 1979, using LED to display results of the replicating pattern which depending on the human or robot interaction. He further developed the idea with his students in the Universal Constructor project, which explored a self-organizing interactive system with each unit can display the state, communicate to adjacent units and pass message to the person who interacts with the model (Frazer, 1995).

Figure 2 The Universal Constructor, working model of a self-organizing interactive environment, AA Diploma Unit 11, 1990.

Even though a number of previous research on the application of CA as design tools, it is still an uncertainty of how designer could translate generic CA into specific design tool (see for example Frazer, 1995; Coates et al., 1996; Krawczyk, 2002; Herr and Fischer, 2004). Frazer criticized that even though demonstrated computational processes and simulate various life-like processed, the discrete nature of the CA system is “not a model of nature and evolution”, and “strictly deterministic in nature” (Frazer, 1995). The self-replicating aspect of the cell is often difficult to be represented in real models, and Conway’s Game of Life as the most popular rules set generally lose its nature when stepping out form the 2D animated grid to transform into 3D architectural form (Krawczyk, 2002). And with 3D CA, despite appeared to provoke architectural spatial qualities, required an intensive research on the rule set and computational power to translate to pragmatic architecture projects (Krawczyk, 2002). The application of computational algorithms in Architecture Design is growing rapidly, with the recent development of A.I. is influencing not only in computer science field but also the generative design approach in architecture. Architects are fascinated with applying computational algorithms like CA in real-world design (see for example Herr and Fischer, 2004; Stouffs and Araghi,


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2016). And with the ‘second digital turn’ toward discreteness in architecture which is formulating by Carpo (2017), the discrete nature of CA is more relevant to the generative design process more than ever. However, before looking at the recent exploration of CA in architecture, an understanding of the bottom-up approach to high-density housing development should be reviewed to build up the contextual framework for any further research.

HIGH-DENSITY HOUSING IN THE DIGITAL AGE. According to Stouffs and Araghi, during the design process of high density housing design, due to the numerous of information and parameter required, architects are typically incapable of design each individual housing unit according to the need of the inhabitants, instead often apply a standardization strategy which aiming for the economies of scale and efficiency optimization (2016). The results are monotonous estate developments with limited uniform building blocks, which often fail to meet user's variety of needs and social dynamicity for a well-being neighbourhood (Stouffs and Araghi, 2016). In the 1970s, Turner formulated his philosophy of housing by people which express the belief that “networks of people can take hold of their own surroundings and order them intelligently without experts to decided what they need” (1976). Taking case study from both underdeveloped and developed countries, a bottom-up approach to housing from individual community is to set against the top-down housing scheme which was imposed by their governments (Turner, 1976). Ward further emphasized the idea by an anarchist approach to housing, seeking "a self-organizing society as a network of autonomous free associations for the satisfaction of human needs" (1983). Tenant take-over strategy was analyzed, with the advantages that this scheme could bring both to inhabitants and to society a greater efficient use of the nation's housing stock was outweighed the disadvantages. These two authors both suggested that the “dwellers control” principle in the design process could produce ‘stimulate individual and social well-being’ (Ward, 1983). Come to the Digital Age, the idea of mass customization replacing the mass standardization in architecture was explored by Carpo (2017), argued that in the future digital techno-cultural environment, standardization is no longer saving money, and masscustomization can be done at no cost. He emphasized that digital mass customization has been “one of the most important architectural inventions of all times”, which from the intention of innovating the manufacturing process of daily use objects (tea ports, tables, buildings) to remodel the technical logic and culture for all dimensions of the current world (Carpo, 2017). The messily micromanaged arrangements which organically and spontaneously adapted and functioned in the pre-industrial societies could be recreated using digital tools like Internet, Big Data and computational algorithms (Carpo, 2017). As a result, digital mass customization could be a response to the heterogeneous demands of the inhabitants in both design and occupation process, against the current mass standardization in housing projects. Furthermore, according to Morrel, the use of computational tool in architectural design in the Digital Age is an adaptation from the computation concept of computer intelligence to the human rationalism with human ratio (2016). The kind of complexity in computational logic are different with the formal complexity, it bound to the intricacy of multilayers of knowledge and discourse. The scale is also an important aspect, as this kind of complexity in architecture can only be explored starting from the scale of a house. Architectural computationalism is always interwoven with the economical and political counterpart, deeply affect the structure of architecture and our social life. And he suggested that architects should understand those technological conditions in order to positively contribute to the situation (Morrel, 2016). From all the point above, the architect of the Digital Age should embrace the diverse needs of individual user in the form generation process of housing design, using the principle of mass customization to create a bottom-up adaptive type of architecture that involve and respond to its inhabitants. To harvest the concept of CA in housing design process, an in-depth analysis on existing models of high-density housing need to be approached in mathematical and computational way. Understanding the need of each individual occupant and the network created by those demands will lead to a logical adaptation of computational method in solving problems.


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CA AS AN ARCHITECTURAL ANALYSIS TOOL Architecture could not be progressed without a profound understanding of the past precedents. This part will examine how CA has been used as an analysis tool for complex existing structure and dynamic urban form. In 1964, Alexander used the primitive concept of CA as the examination for Fit and Misfit of architectural form with its surrounding, and elaborated the sources and the qualities of processes that define a good fit form in its context. By study the existence of traditional house like the Mousgouand Hut and conceptualize the fitting simulation in a binary operation to apply in the form-making process, Alexander was testing each variable is in a state of either fit or misfit toward a final stage of equilibrium (1964). The unconsciousness culture, as a gradual process of adaptation and fitting, gave evidence and explanation of traditional vernacular architectures for this homeostatic approach in contradiction with the self-consciousness process in form fitting. Through a direct relation with materials, context and feedback, the agent “recognizes and react to failure in an instinctive way to achieved fit form without any special ability” (Alexander, 1964). Alexander's mathematical approach to urban patterns has widely influencing both in architecture and computer science field, which built up the foundation for the implication of computational power in analysing architecture later (Patternlanguage, 2006).

Figure 3.a. Illegal building extensions in Hong Kong; facade evolution Figure 3.b. Hardware cellular automata model with building extension modules , Herr and Fischer, 2004

With modern housing architecture, Herr and Fischer (2004) have researched in the application of CA for the adaptation of user in vernacular high-density architecture and proposed “a machine-readable architecture model that accommodates ongoing change in software and hardware “. Taking the illegal façade extension in Hongkong as a case study, the research contributed a better understanding of the process behind the dynamic growth of architecture even after design and construction finished. By building up a table top size model of an intercellular relations system, with two users interact simultaneously to “maintain an overall equilibrium of simulated user satisfaction “(Herr and Fischer, 2004). On the one hand, the paper has not explored further into the reason behind the actual need for the illegal extension and formulated it to be able to perform analysis of growth in the structure. The use of internal connections represents for old telecommunication system have little to no effect on the real-life decision of those façade extensions, therefore the research still has not succeeded in delivering a clear understanding of this phenomenon to apply the computation logic. On the other hand, the projects succeed in deliver message that adaptive architecture of constant change could work.

CA AS AN ARCHITECTURAL DESIGN TOOL The rapid developments of computational logic in architecture designs demand clear evidence of intelligent application in the fields. In order to apply the CA logic in the design process, architectural parameters need to be clearly formulated and simplified to become fundamental rule sets of this generative system.


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Figure 4 Cellular Automata Game of Life, AADRL Workshop, 2009

From the design point of view, according to Herr and Fischer, the unpredictable nature of the CA generated patterns has intricated spatial qualities which also broaden the imagination of the designer. In the design process, the designers has explored the undeterminable aspiration and logical examination of the complex generated results (2004). For example, AADRL workshop (2009) used the Game of Life rules to create a self-organizing and self-assembly systems, to explore the future application in architectural design. The voxel form was replaced by truncated octahedrons, and through analyzing the system, numeric data could be obtained and interpreted. A change in the morphology of generative field finally created the desired result (Bonjovic, 2009). In addition, Hansmeyer (2009), with the work on Voxel-based Geometries Cellular Automata, has proven that with generative design, the undrawable form can be the result of a deterministic process which there is no randomness involved but it is not entirely predictable. The architect should not only design an object but also the process to generate that object. Through the use of CA, Hansmeyer generated five pavilions, and concluded that their application is “better suited to generate components of a structure rather than the structure itself� (2009). However, the generated forms from both projects are still very abstract and difficult to imagine what structure could be extracted or created, yet still belong to the design realm rather than architecture.

Figure 5 Five Pavilions Generated Using Cellular Automata, Michael Hansmeyer, 2009

From the architecture point of view, Coates et al. (1996) have explored the use of 3D CA in the process of finding new aesthetic architecture form in the new Digital Age. Using CAD package, they have experimented with altering and extending the simple rules of Game of Life to generate spatial organization by array of voxel, encoding the different components of the emergent form. By adding environments parameter like lights which gave direction in the growth process of the structure and provided new


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relationship between function and space. Through voting rules, the pattern grew in accordance with spatial locations of cells, then apply the death, birth, and survival for counting rules (Coates et al., 1996). Nonetheless, this system has created raw forms which still an abstract and not properly addressed the functional requirement of architecture such as supports and connections. Krawczyk (2002) argued for the utilization of the mathematical constructions and concepts of Game of Life to investigate the process of generating architectural forms. His research attempt to apply a hybrid method of using CA as a technical layout of architectural elements and using it underlying concepts as an inspiration for the project. The experiment attempted to solve the issue of horizontal connection by manually offset the cell outward or change the shape of the cell (Krawczyk, 2002). However, his proposal of adding columns to address the lack of vertical supports and adding a cover for the whole structure limited the generative discrete grow of CA, and the final figure is merely a captured of the CA raw data and translated literally into architecture.

Figure 6. Using CA to generate multiple design options based on footprint locations, Stouffs and Araghi, 2016

With the advancement in computational design theories and software, the recent researches are becoming more realistic and relevant to architectural design process. Start by classifying the cell from the apartment and circulation units, Stouffs and Araghi’s (2016) project initiated with a clear rule set, which is a simplified typical floor plan of high-density housing. Taking accessibility both horizontal and vertical in a more automated manner, the project uses the basic of Moore neighbourhood rule to generate a CA logic of access to all cells in the given lattices. Then, natural light was considered as the second parameter, as every single cell should have access to light. In the end, the research concluded with the generation of form from a specific site, a boundary, and specific architecture requirements. The research has succeeded in translating the CA logic in the design process of a conventional architectural project, with parameters such as access and light, which have an actual impact in the form finding process generated by an automated procedural (Stouffs and Araghi, 2016). Nevertheless, the idea of customization and adaptivity have not been fully embraced, which makes the final product remains static rather than a dynamic adaptation.

Figure 7. Architecture of high-density residential buildings, Hague, The Netherlands, Stouffs and Araghi, 2016


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CONCLUSION The evolution of Cellular Automata from a purely mathematical theory to its application in Architecture Design in the last decades have shown a positive progress of using computational ideology in analyzing and solving problems, which are unimaginable for traditional approach. On the one hand, only by looking in-depth into existing conditions of high density architecture through the lens of computationalism, the architect could be able to parameterize and digitalize the contextual framework to apply a computational algorithmic approach. On the other hand, more critical researches need to be executed to further develop physical built prototype with the capability of adapting to the individual need of users. Finally yet importantly, robotic manufacture and assembly should be researched in parallel, to fully embrace the bottom-up approach to high-density housing in the Second Digital Age.

Image References Figure 1: Krawcyk, R (2002), Architectural Interpretation of Cellular Automata. In: Soddu, C. (ed.): The 5th International Conference on Generative Art 2002.Generative Design Lab, DiAP, Politecnico di Milano University, Italy, pp. 7.1 & 7.5. Figure 2: Frazer, J. (1995). Themes VII: An Evolutionary Architecture. London: AA Publications. Front Cover.

Figure 3.a & 3.b: Herr, C., Fischer, T. (2015) Using hardware Cellular Automata to simulate use in adaptive architecture. Available at https://cumincad.architexturez.net/system/files/pdf/507caadria2004.content.pdf. pp. 5 & 7.

Figure 4: Bojovic, M. (2009). Cellular Automata In Architecture / AA Workshop - eVolo | Architecture Magazine. [online] Evolo.us. Available at: http://www.evolo.us/architecture/cellular-automata-in-architecture-aa-workshop/ [Accessed 2 Jan. 2018].

Figure 5: Hansmeyer, M. (2009). Michael Hansmeyer - Computational Architecture: Cellular Automata. [online] Michaelhansmeyer.com. Available at: http://www.michael-hansmeyer.com/projects/voxels_info3.html?screenSize=1&color=1#undefined [Accessed 2 Jan. 2018].

Figure 6 & 7: Araghi, S., Stouffs, R. (2014) Exploring Cellular Automata for high-density residential building form generation. Automation in Construction 49, pp. 159 & pp.161.

References Alexander, C. (1964). Notes on the Synthesis of Form. Harvard University Press, pp.26-54.

Bojovic, M. (2009). Cellular Automata In Architecture / AA Workshop - eVolo | Architecture Magazine. [online] Evolo.us. Available at: http://www.evolo.us/architecture/cellular-automata-in-architecture-aa-workshop/ [Accessed 2 Jan. 2018].


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Coates, P., Healy, N., Lamb, C. and Voon, W. L. (1996). The Use of Cellular Automata to Explore Bottom Up Architectonic Rules. In Eurographics Conference, Imperial College of Science and Technology, London

Carpo, M. (2017). The Second Digital Turn. 2nd ed. The MIT Press.

Frazer, J. (1995). Themes VII: An Evolutionary Architecture. London: AA Publications.

Gardner, M. (1970), The Fantastic Combinations of John Conway’s New Solitaire Game of “Life”, Scientific American, 223, pp.120123

Hansmeyer, M. (2009). Michael Hansmeyer - Computational Architecture: Cellular Automata. [online] Michael-hansmeyer.com. Available at: http://www.michael-hansmeyer.com/projects/voxels_info3.html?screenSize=1&color=1#undefined [Accessed 2 Jan. 2018].

Hardingham, S. (2003). Cedric Price Opera. Chichester, West Sussex, England: Wiley-Academy.

Herr, C. and Fischer, T. (2004). Using Hardware Cellular Automata to Simulate Use in Adaptive Architecture. In: H. Lee and J. Choi (Eds.). CAADRIA 2004 Proceedings of the 9th International Conference on Computer Aided Architectural Design Research in Asia, pp. 815-828

Krawczyk, R. (2002). Architectural Interpretation of Cellular Automata. In: Soddu, C. (ed.): The 5th International Conference on Generative Art 2002. Politecnico di Milano University, pp. 7.1-7.8.

Khalili Araghi, S. & Stouffs, R. (2015). Exploring Cellular Automata for high-density residential building form generation. Automation in Construction, 49, pp.152-162.

Patternlanguage.com. (2006). PatternLanguage.com. [online] Available at: http://www.patternlanguage.com/ca/ca.html [Accessed 8 Jan. 2018].

Turner, J. and Ward, C. (2017). Housing by people. New York: Marion Boyars.

Schrandt, R. & Ulam, S. (1970). On Recursively Defined Geometrical Objects and Patterns of Growth, in A. Burks (ed), Essays on Cellular Automata, University of Illinois Press, Urbana, pp. 232-243.

Von Neumann, J. and Burks, A. (1966). Theory of self-reproducing automata. Urbana: University of Illinois Press.

Ward, C. (1983). Housing, an anarchist approach. London: Freedom Press.

Wolfram, S. (2002). A new kind of science. Champaign, IL: Wolfram Media.


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