As a “boundary object” [Wenger-Trayner 2017] at the intersection of architecture, com- puter science and engineering, different types of value can be attributed to Typogenetic Design. These types are “immediate value”, “potential value”, “applied value”, “realised value” and “transformative value” [Wenger-Trayner 2017]. In summary, the immediate value of Typogenetic Design is the increased efficiency of shape design by integrating performance measures and emergent representations in a holistic design approach. The potential value of the investigated mechanisms were discussed in Chapter 4. Here, the potential applications of Shape Comparison and Online Classification for Architectural Digital Libraries, Design Recommendation System and Organisational Creative Decision Support Systems were described at the end of Chapter 4. Those applications can be de- veloped by architectural researchers with programming and software engineering skills. In 5 different case studies showcase the applied value generated by this research project for design of structural nodes in different contexts and shape design in both automated and semi-automated mode. This Chapter7 discussed the realised value of my research as process useful for interactive generative design, interactive mass-customisation and inte- grated decision support. Finally the transformative value of Typogenetic Design will be explained in the following Chapter8in reference to the User Experience Evaluation Study detailed in ChapterD.
I argue that a collaborative exploration of shape spaces using Typogenetic Design would be most beneficial to the client and the designer, because they would share the reflective process. In this case the role of the designer is two-fold: (a) the designer provides a representation as an expression of a geometric principle or rule-set and therefore designs a meta-expression of shape that can be used to express a guiding principle or a boundary to the geometric variability of the shapes expressed by Typogenetic Design and (b) assist
the client using aesthetic guidance and provide professional advice by using arguments to evaluate or justify individual shapes as expressions of the representation. A certain level of understanding of architectural design and underlying principles is required in using Typogenetic Design.
CHAPTER
8
Conclusions
“Nach dem Spiel kann jeder wissen wie man haette spielen muessen.”
–Hans Braunwarth
In this chapter, I shall present the main contributions of this thesis and conclude with reference to some final remarks. I also present the most significant insights gained during this PhD study from the perspective of architectural design research and their contribu- tion to architectural design practice. The present dissertation contributes to architectural design by proposing an aesthetic system introducing novel input mechanisms for design space exploration to Generative Design (GD) within the framework of Typogenetic Design. The research focused on the introduction of interactive mechanisms and communicative apparati to foster collaboration in Human-Computer-Interaction (HCI). Shape Compar- ison and Online Classification were used to augment evolutionary search with additional capabilities for creative input by the designer. Those interactive mechanisms contribute to aesthetic guidance in architectural optimisation. The use of this aesthetic system in GD allows designers to interactively explore emergent representations in a morphological search.
8.1
Contributions to Architectural Practice
In the course of completing the present PhD study, I experienced a qualitative shift in my understanding of design agency, subjectivity and authorship in computational design. The understanding of Artificial Intelligence (AI) as a conversation partner in computational design systems led me to a comprehension of augmented, collaborative, combinatorial decision making as a mutually informing process between the self and the other. This reciprocal augmentation of the self using architectural optimisation, evolutionary search and machine learning on the one hand, and on the other, using HCI for supporting eval-
uation of aesthetics and other hard-to-evaluate criteria, pointed to a process capable of serving architecture’s need to create certain aesthetics, spatial configurations and propor- tions. The shift from optimisation to learning as a computational paradigm revealed the qualitative change that is occurring with respect to collaboration with computational sys- tems: a shift from the mere adjustment of the behaviour of the system to an adaptation of the underlying complex processes, and to the demands and requirements of the design conversation. This qualitative shift was spawned by the increasing emphasis on perfor- mance and sustainability criteria in architectural design. A reassessment of optimisation processes is necessary to address the full scope of architecture, including aesthetics and the use of intuition during decision-making. Also, application of tacit knowledge needs to be considered in designing flexible and adaptive interactive mechanisms that allow to make decisions based on choice. When the designer communicated her or his choices based on desirability and aesthetic delight, the system response was not only behavioural, but analytic in learning implicitly about the rules, characteristics and features that might drive this articulation of preference based on the computational representation.
Moving forward from the parametric design paradigm, exploring the geometric varia- tion of pre-defined combinatorial design spaces, application of Typogenetic Design allows designers to interactively explore design spaces provided by the algorithmic expression of GD. This choice was significant, because it opened up an avenue for the use of emer- gent representation as basis for the investigation of online browsing capabilities using shape recognition. Thereby, the concept of ‘ratiocinatio’, described by Vitruvius in [Pollio 1914], as a combination of craftsmanship and playful calculation, could be mapped onto the interactive computational design system as a combinatorial game. The architectural expertise and craftsmanship of the individual designer playfully unfolds in the interaction with the Typogenetic Design system. The underlying calculation integrates performance criteria into the exploratory search. The emergent properties of GD avoid simple repeti- tion and foster the learning of similarity, diversity and distinctiveness of design solutions. In summary, the choice for playful interaction during exploration of a variety of shapes allowed the choice-based application of tacit and professional knowledge. This was a significant step toward a shift in understanding of the architect in the context of GD.
The role of the architect in the context of Typogenetic Design is mainly the role of the meta-designer that (a) sets goals for the design process, (b) defines criteria for performance evaluation and (c) designs and refines the geometric representation during the process along with the underlying geometric principles and rules. The use of the Typogenetic Design process is limited to the shape generation based on the goals, criteria and representation defined by the architect. Additionally, the architect can advise non- expert users during design tasks.
This PhD research addressed the application of architectural computing in early de- sign stages by providing a creative, engaging and easy-to-use design process that facilitates
interactive GD as an initial morphological search. The intuitive use of this holistic process, which combines quantitative and qualitative design criteria, was increased by introducing interactive mechanisms developed during Typogenetic Design. As a result, the intuition of the designer and the expert knowledge that she or he embodies can contribute directly to the evaluation of the presented solutions. Therefore, the designer steers the vehicle of the adaptive system toward the intended design solution. The use of exploratory search in early design stages could be used as a process of inspiration that can help to discover novel visual details, elements and shapes during spatio-morphological communication of architectural geometries.
Using a sophisticated interactive GD process revealed a quality of designed artefact that is not usually seen in other design processes. Expediency, delicacy, elegance and intricacy of geometric morphological details provided the resolution needed to explore the design potential of additive manufacturing. This increased potential to refine geometry iteratively and in reference to both qualitative and quantitative performance criteria was based on an efficient computation of sets of spatio-morphological and highly complex architectural geometries.
8.2
Typogenetic Design
The key contribution is the theoretical framework of Typogenetic Design based on the core mechanism of Shape Comparison in a broad interactive approach facilitated by Online Classification. This adaptive framework for creative design built on the interactions, explorations and learning experienced on my research journey toward increased efficiency in user interaction during interactive GD. The chosen approach addressed the complexity of design requirements with respect to multiple performance criteria during early design stages by using human-in-the-loop technology for design augmentation.
The provision of performance data early in the decision-making process during archi- tectural design increases design effectiveness. Semi-automated design allowed the designer to navigate the form-finding process, while benefiting from the computational power for calculations trading off quantitative criteria in the background. The investigated mecha- nisms for designer interaction allowed the hybrid system to evaluate aesthetic preferences during GD. As a way to explore design options and overcome the limitations of automated design processes, an Aesthetic Support System was introduced for aesthetic guidance. This aesthetic system contributed to the stream-lining of GD by taking advantage of AI tech- nology and increases in computational power. The Aesthetic Support System adapted to user preferences and choices by using real-time machine learning (Online Classification) and computer vision (Shape Comparison) to analyse design decisions.
Correspondingly, Typogenetic Design made it possible to address qualitative aspects of design while simplifying the handling of architectural optimisation. Designer fatigue
is already a metaphor that is used frequently to describe the effects of losing interest during extensive designer evaluation, and because of decreasing cognitive effectiveness during interactive computational processes. The use of a broad interactive approach in Typogenetic Design allowed me to significantly reduce the amount of user input necessary to effectively steer the GD process. Therefore, designer fatigue was less relevant for the user evaluation in architectural optimisation or GD with large solution spaces (n.b. question 10, sub-question 12, AppendixD). Providing control over the aesthetic expression of building designs in generative processes during periods of automation was crucial for the convergence of the computational process toward a specific shape that satisfies the designer (n.b. question 1 and 3, AppendixD). This way, Typogenetic Design as intelligent interface supports creative design in architecture. As a result, a coherent shape style can be realised by use of Typogenetic Design.
Two characteristics of the architect’s or designer’s role in using Typogenetic Design shall be considered. First, in the human-in-the-loop system, the architect or designer ex- ercises supervisory control over the design system by setting goals, solving the design task and reacting to unexpected behaviour of the computational system. Second, the architect is meta-designer, designing the geometric representation based on the design case at hand. The architect interacts with Typogenetic Design based on the experience and professional knowledge gained as practitioner. The focus here is on the early stages of architectural design, using the design system to explore geometric variety as application in creative processes and as creative decision support. During the interactive use of Typogenetic Design, the architect uses her or his professional understanding to link the shape design process to the context of the design case, including client needs and the relationship to the discipline of architecture.
Analysis, evaluation and synthesis were integrated in performance-based digital pro- cesses. Consequently a computational approach to Architecture, as described by Vitruvius in ‘The ten books on architecture’ [Pollio 1914], was embodied. “Firmitas” - the concern of the architect with structural stability of architectural artefacts - was addressed by in- tegration of structural optimisation into a multi-staged design strategy. “Utilitas” - the utility of processes and products for specific design cases - was approached by addressing the practical issue of tectonic articulation. “Venustas” - aesthetic expression and pro- portions that needed to be considered in architectural design to provide the expected beauty, delight and elegance - was resolved by addressing the phenomenological articula- tion of respective rules in training machine learning models and semiological articulation of aesthetic aspects by processing images to provide aesthetic guidance.
An architectural inquiry using Typogenetic Design as an active tool involved a search for novel design solutions and design inspiration in contrast to an optimisation of concepts already present. This step is expressed in the metaphor of the primordial soup that gave birth to creatures, species and taxonomies of individual expressions of organisms. In
architecture this transition was “from typology to topology” [Schumacher and Zheng 2017] and “from parts to particles” [Schumacher and Zheng 2017] - a conceptual change from pre-defined parametric geometries to GD, which can now be explored more efficiently to reveal the full potential of GD for design purposes.
AI is already changing the way buildings are designed, and it has transformed the architecture, engineering and construction industries. Many fields and industries have adopted this technology for analysis, evaluation and synthesis in a wide range of appli- cations. Despite the AEC industries’ traditionally slow adoption of novel technologies, integration of computational technology into design processes has accelerated during the last decade. Still, a paradigmatic turn in the use of CAD systems toward more creatively engaging solutions will enhance the suitability of CAD software during early design stages [Mitchell 1989]. Such a system would be capable of enhancing designers’ ability to “cal- culate design” [Stiny and Gun 2012], and I view this research as a stepping stone on the way toward such creative design systems.
Engaging designers in MCO means that the optimisation process needs to be designed in a way that is interesting and motivating during usage (n.b. Figure D.2 Appendix D). This can be facilitated by providing mechanisms to interact creatively with optimisation processes (n.b. Figure D.3and FigureD.9sub-question 3, AppendixD). The dissertation argues that computational systems for designing are engaging, when they adapt to designer interaction and reduce redundant input. As a result, MCO can be used creatively with limited programming experience and skills (n.b. Figure D.7 sub-question 8 and Figure
D.9 sub-question 8, AppendixD).