Draft of Abstract for ACADIA 2008

multi-scalar reciprocity as a model for bio-inspired design

How can the feedback loops found in natural systems be harnessed to help us navigate the difficult and sometimes conflicting needs of sustainability, economy and delight in architecture?

Biology has been an inspiration to the architecture and engineering professions for centuries because of its elegant resolution of complex problems. As such, the imitation of natural systems – either in look or in operation – is nothing new. Only lately, with greater understanding and the use of computers, have designers been able to mimic more complex natural phenomena for use in high performance designs.

One of the digital techniques being developed lately is the use of localized adaptation to generate form. The enormous potential of this technique, namely the ability of design elements to self-organize, is only partially tapped by most methods. The most common method, based on Darwin’s theory of natural selection, simulates the phenotypic response of an organism to its immediate environment. However it is only a one-way relationship: The part is effected by the specifics of its surroundings, but does not affect the whole.
In actual operation, natural systems have been observed to be much more reciprocal. Not only does the part adapt to the whole at a local scale, but the small result of its role in the system has an aggregate effect: The whole also adapts, sometimes catastrophically, based on the action of many parts. The feedback loop this creates is responsible for the robust self-organization found in many natural systems, and results in the elegant solutions that are so inspiring to architects and engineers.
The process of architectural design already involves feedback loops, as it attempts to negotiate the often-conflicting requirements of sustainability, economy and delight. Traditional iterative methods are effective, but a computational process abstracted from the study of natural systems would be extremely valuable for use in complex high-performance designs. Such digitally assisted feedback loops would allow designers to more easily find design solutions which satisfy extremely ambitious sustainability goals and resolve them with subjective design criteria.
This research builds off of the theoretical groundwork of Georges Canguilhem, in his discussion of the “Milieu”, and of Darwin’s and Lamarck’s theories of biological morphogenesis. It also draws from Reyner Banham’s writing on the use of mechanically controlled temperature gradients to define space (in place of physical barriers). Steven Wolfram’s Cellular Automata and their distillation of part-to-part relationships down to a set of very simple rules also provides some inspiration in designing an algorithm to achieve the feedback loops described above. Alan Turing’s work on chemical morphogenesis and reaction-diffusion equations is also of some interest.
To develop a computational design methodology for architecture, I have studied biological systems that exhibit the desired feedback at a variety of scales. I found that many such systems rely on chemical cues – for example chemotaxis – to transfer information between separate parts. This ambient communication medium is physiologically independent of the communicating organisms, and has a global aggregate presence as well as a direct local one. As such, reciprocal feedback is facilitated across a multiplicity of scales. The chemical cue system is easily abstracted to an algorithmic model in the form of data packets – small pieces of information combined with location that are both created and consumed in a dynamic milieu.
The focus of this research is the development of a digital design methodology, based on the above study of chemical communication and feedback, which employs a milieu of ambient information to achieve multi-scalar reciprocity. The research includes a study of relationships between elements found in selected natural systems, and assessment of which relationships are analogous to those found in architectural projects. The result is a computational methodology, using scripting, to simulate the localized awareness of parts in complex natural systems. Proof of concept is shown as the digital methodology is applied to the Solar Decathlon – a national competition to design a small residential project with high performative requirements.