Chapter 3: Early Software Developments and their Principles

CHAPTER 3:

Early Software Developments and Their Underlying Principles

14

CHAPTER 3: EARLY SOFTWARE DEVELOPMENTS AND THEIR PRINCIPLES

The main intention for designing generative design software was to provide a reasonable explanation for the set of choices made while designing and justify the final outcome through comparison with other possible variations.

Secondly, it could enable the designer to explore unexpected results engendered by his initial idea. Thus, leaving room for unconventional, unpredictable solutions to be discovered.

Celestino Soddu developed his “experimental representation of complex, nonlinear systems to manage multiple bifurcations and variations in a morphological sense” (Soddu, 20 Years ARGENIA evolution, 2009).

In 1979, he developed a software which used 2D reverse perspective to generate 3D models. Along with this, his experimental research on representation made him suggest the use of fractal geometry for creating a natural environment. (Soddu, 20 Years ARGENIA evolution, 2009)

3.1 Generative Design Processes outlines by C. Soddu

Shortly after this, Soddu developed his vision for generative design software. Objectives of his vision for generative architecture were devised by studying the challenges he faced with developing algorithms. The following were the challenges faced:

3.1.1. Designing a platform of architectural precedents

A database or algorithms was required. The program had to be taught about the existing architectural styles. Innovations can only be built by permutation and combination of existing algorithms. Knowledge of past precedents and their application in combination with the abstract idea could generate unpredictable design solutions.

It is like applying Turing’s experiment to architectural design. In other words, giving the ability to think to a computer. Only with the ability to decide can a computer algorithm account for subjectivity in the design

process.

15

1.1.2. Designing an engine which could produce progressive logics of transformations (Soddu, 20 Years ARGENIA evolution, 2009)

For creating a complex overlay, the parameters and their subsequent choices are required to function in an orderly manner. Stratification is done of these choices. This helps to classify, prioritize and merge parameters to create a hierarchy.

After stratification, existing systems are interconnected to form a network. Each algorithm/design choice is like a neuron and we are looking at developing a network which functions like a brain. Variations in this network and how they interacted with each other would give rise to a sequence of algorithms developing more algorithms. Thus, a progressive network of transformations.

The final step would be to record the results of these transformations and let them operate as driving factors of the design process.

1.1.3. Moving from Heuristics to meta-heuristics

Heuristics refer to a set of solutions which are formulated by their success in past precedents. These are thumb rules which deal with a generic set of problems. Solutions generated by thumb rules are faster but may not always be the optimum solution in every case. Results generatedbyfollowingheuristicapproacharepredictableandinefficient because they are not tailor- made for the set of problem in consideration (Nagy & Villaggi, Generative Design for Architectural Space Planning, 2018)

On the other hand, ‘metaheuristics’ refer to “a set of optimization techniques that for a given complex problem, can find a set of overall best solutions by iteratively sampling solutions and using performance criteria to generate better and better outcomes” (Nagy & Villaggi, Generative Design for Architectural Space Planning, 2018)

16

The main objective of introducing metaheuristics was to move past the traditionally accepted layouts. For achieving this, subjectivity had to be introduced in the generative algorithms.

“Design processes which didn’t deal with a set of complexes overlapping challenges were usually axiomatic, linear and did not yield innovative results” (Soddu, 20 Years ARGENIA evolution, 2009)

To achieve subjectivity, complexity had to be added and it was done by producing an array of complex algorithms, progressively producing more algorithms. Basically, it was the algorithm teaching itself to make more algorithms before narrowing it down to reach desired results.

1.1.4. Engaging subjectivity by giving an identity

To make a project seem native of its surroundings, the last set of subjectivity introduced into the program was engaged by giving it an identity. Identity might be an artificial conscience developed of the natural environment or the ingenuity of the original idea. Identity would be the essence the designer wants to convey through its design.

3.2 Development of Basilica

After seven years of experimental research on the above-mentioned objectives, Soddu developed Basilica in 1986. This is a predecessor of Argenia which concentrated on development of urban surroundings for medieval towns and cities. These urban environments were usually translations of work by Simone Martini and Giotto di Bondone (Soddu, 20 Years ARGENIA evolution, 2009).

Simone Martini is responsible for the development of Gothic Style while Giotto di Bondone was an artist and architect in Florence. Their descriptions and paintings have been used to generate ideal medieval towns. Multiple variations were generated on the basis of their vision of medieval towns.

17

Figure 8: Image used as reference for creating algorithm to generate Giotto’s description of medieval town (Soddu, Generative City Design: Aleatority and Urban Species, 2020)

(a)

18

(b)

(c)

Figure 9 (a-c): Different iteration of Giotto’s visualized medieval town generated using Basilica (Soddu, Generative City Design: Aleatority and Urban Species, 2020)

The engine, basilica, could generate multiple variants of subjective transformations, modifying itself in second and third dimension. However, it was limited by the technology of that time. Any changes made in the program yielded an output overnight. To make further changes, another night was required for the program to exhaust its set of options.

“Themaindifficultyofthesefirst experimentationsofthemiddleof‘80s was the time due to verify the system. Because the screens with green or yellow phosphorus were at low resolution, the only possibility was to directly trace a representation through the pen plotter. I launched in the evenings the program and the subsequent mornings I got up for seeing

19

the result. Updated the program Ihad to wait a lot for verifying it again.” (Soddu, 20 Years ARGENIA evolution, 2009)

However, with practice handling transformations became easier.

“Basilica worked on three foundation principles:

1. Identifying organizational paradigms of architecture able to define events, relationships and interferences

2. Tracing initial events that define, in first approximation, the dimensions and the orientation.

3. Managing ranges of geometric transformations, each one able to increaseoneofthefunctional / aesthetical / symbolicaspects and to push the events toward my architectural Vision.”

(Soddu, 20 Years ARGENIA evolution, 2009)

20

3.3 Collaboration with Cellular Automata

Basilica worked with transformations which worked simultaneously in the metamorphosis of single events and that of the whole project. This led to redundancy in these logics. The program could not determine when and how these logics of transformations should be activated or what to choose in a particular situation (Soddu, 20 Years ARGENIA evolution, 2009). Thus, Cellular Automata was incorporated in the code of the program. This generated topologic models which adhered to the identity of the project. This determined which logics were more probable to be reflected in the design by analyzing its starting point in the code.

The starting point ensured that the results generated could be recognized as the belonging to the same species but were unpredictable due to nonlinear complex systems which led to its discovery. (Colabella, 2006)

Figure 10: Paradigms generated by inclusion of Cellular Automata with Basilica (Soddu, 20 Years ARGENIA evolution, 2009)

“Basilica I used specific geometric parametric algorithms, algorithms managing the transformation of event's figure by moving from a dimension to another, Cellular Automata and parallel progressions of transformations of single events that dynamically interact with others, as flocking of birds, and structures of repetition of the same algorithm applied to the same event, as fractal approach. But none of these methods is primary. The peculiarity of my approach is “how” I use them all together. It is the expression of how it's possible to effort single, unexpected and unpredictable requests with the aim to fit my Vision of Architecture. The main question is not only the tools but the right aim.” (Soddu & Colabella, Generative Art and Architecture, n.d.) 21

3.4 Model Development after 1988

Thedevelopment incomputertechnology enabled Soddu to recordhis iterations and publish them together in his book Città Aleatorie, which is a compilation of urban environments generated by Basilica and its successor Argenia.

Figure 11: Screen dumps of basilica in 1990 (Soddu, 20 Years ARGENIA evolution, 2009)

Breakthrough however was made by implementing and evolving Argenia by applying it to the interdisciplinary filed of Generative Art. Basilica was developed and used for industrial design, product design and to create art. The main aim was to make Basilica an open software which was user friendly and reached out not only to designers but to a larger demographic. The interface was developed to ensure that the user could efficiently apply it with primitive knowledge of algorithms.

Figure 12: Chairs designed using Argenia (Soddu, 20 Years ARGENIA evolution, 2009)

“In 2001, Soddu developed and experimented the feasibility of a direct interaction between my generative software Argenia and rapid prototyping devices, and therefore with industrial devices at numerical control. He successfully managed the possibility to directly produce unique objects by using these devices. Argenia opens this possibility by

22

generating in real timeuniqueSTLfilesusable for producing asequence of unique objects.” (Soddu, 20 Years ARGENIA evolution, 2009)

3.5 Development of Artificial DNA: Introduction to Argenia

The algorithm, over the years of 20 years of experimental research by Celestino Soddu and Enrica Colabella, developed into a DNA. It was found during research that minimal changes in a set of preexisting algorithms could lead to the transformations bearing a unique identity. Thus, a complex overlay of 20 years’ worth of algorithms, i.e., the DNA was compiled and made capable of customization at the behest of the user.

Argenia became an open-source software which catered to the needs of all designers, architects and artists. “Domus Argenia has the aim to develop exchange among different creativeness and different disciplines in a cultural approach focusing on Identities, the subjective creativeness and different cultural heritages.” (Soddu, 20 Years ARGENIA evolution, 2009)

For designing with Argenia, Soddu outlined six fundamentals for development and modification of the base algorithm.

1. Identification of initial Idea and comprehension of the ‘vision’.

2. Identification of design moments: Determining how the spatial transformation or molding of form would take place.

3. Introducing subjectivity in the algorithms by adding preferences and elaborating design vision/concept. Thus, developing an identity of the project.

4. Setting up a hierarchy in the algorithms, creating a complex array of progressively transforming algorithms.

5. Evaluating the generative process on the basis of the outcomes produced and modifying paradigms.

6. Exploring representations of the idea produced by the engine and optimizing results for the desired result with maximum efficiency.

(Soddu, Teaching Text : Generative Design, n.d.)

23

3.6 Learning from the development of Argenia

The field of generative design established some postulates on the basis of the research done for the development of generative software, Argenia. The prerequisites for the development of any project in a generative environment became clear. Subjectivity and context could be defined in computational terms and it could be controlled how and when they would affect the result of the project.

Even though the intangibles were well defined to the software and made clear to the user, generative design failed to be incorporated as a design method in architectural practice.

The approach relied on giving an architectural understanding to the engine. This was done by programming the learning derived from past precedents. However, at that time digital documentation had just begun and the approach failed due to the lack of a digital database.

Second major cause of failure was the processing speed of computers. Any change made in the code was witnessed in the result after hours or days.

Automated design software has a higher probability to be incorporated and efficiently used in architectural practice today. This is mainly due to the development of BIM (Building Information Modelling) and parametric softwares. The development of these two programs in the field has given an insight into Celestino Soddu’s original principles. Gradually over the years we have achieved the prerequisite database required for generative algorithms to optimize workflow.

The next chapter discusses the collaboration of parametricism and Building Information Modelling in advancement of generative design software.

24