Critical Practice, a cluster of artists, researchers and academics hosted by Chelsea College of Art and Design has recently commissioned Ola Wasilkowska and Michal Piasecki to design a temporary spatial intervention for their Parade event. The event took place on 21-23 May, 2010 at Rootstein Hopkins Parade Ground in London.

The structure, called Assemblage in Public compromises computational design strategies with a low-tech assembly of repeatable components on site. The project is rooted in an idea that a repetition of a few simple rules is able to construct complex geometry, which can host different functions.

The core structure of the intervention was obtained through multi objective optimization with genetic algorithms. The optimization was conducted with a purpose built software written in Processing. The goal was to distribute the components according to a predefined “shadow map” and to keep them structurally stable at the same time. 4320 crates where used in total. Below are some of the individuals from one of the middle generations.

After the core was erected according to the plans extracted from the optimized form, everyone was invited to contribute to the intervention by adding on furniture. These where meant to be integrated and dissolved in the structure, so that discovering them may be surprising, but at the same time when they start to be used, they always prove comfortable. For this part of components assembly, there was no pre-defined layouts, so the structure started to crawl in diverse directions.

The low-tech crate component enabled the mixture of an evolutionary search for an optimal form with collective intelligence to create an attractor intervening the everyday use of the public.

Images: courtesy of Marsha Bradfield and Neil Cummings from Critical Practice.

“A Redefinition of the Paradox of Choice”, a paper co-authored by Michal Piasecki and Sean Hanna, was accepted for the Design Computing Cognition conference 2010 (DCC’10).

In the paper builds upon Barry Schwart’z definition of the paradox of choice. The abstract outlines our proposition of reconsideration of the paradox and positions the Breeding Objects Experiment 1 in this context:

Abstract: Barry Schwartz defined the paradox of choice as the fact that in western developed societies a large amount of choice is commonly associated with welfare and freedom but too much choice causes the feeling of less happiness, less satisfaction and can even lead to paralysis. The paradox of choice has been recognized as one of the major sources of mass confusion in context of the B2C online mass customization. We propose to redefine the paradox of choice with an emphasis on the meaning of choice in conjunction with the amount of available options, rather than just the quantity of choice. We propose that it is the lack of meaningful choice, rather than an overwhelming amount of choice, that can cause customers’ feelings of decreased happiness, decreased satisfaction and paralysis. We further propose that since users themselves are often not able to explicitly define what constitutes a meaningful choice, the task they face belongs to the category of ill-defined problems. The challenge for mass customization practitioners is thus not to limit the scope of choice, as has been suggested in previous literature, but to provide users with choice that is relevant to them.

We further discuss two computational approaches to solving problems related to the redefined paradox of choice in the context of the B2C mass customization. The first is based on recommender systems and the second is an implementation of artificial selection in genetic algorithms. We present findings of an empirical comparison of genetic algorithm and parametric product configurators. We find that the genetic algorithm tools, which allow users to move through a solution space by recognition of meaningful options rather than their definition, appear to be more popular among the users when it comes to browsing through solution spaces with larger number of dimensions.

Green2 is a new polish architecture and design magazine focused on sustainability. Their second issue is on biomimetic design and Michal Piasecki was asked to write an article on computational means of introducing biomimetics into the design process.

The article begins with the discussion of Andrew Kudless’ P-Wall project. An inquiry which seems to be deeply rooted in Frei Otto’s research on material computation. Michal further argus that biomimetics is about mimicking natural processes of formation, rather then natural forms themselves and that simulation of evolution and the process of learning falls into this category as well. The discussion of evolutionary algorithms starts with Karl Sims’ early experiments on breeding three-dimensional forms expressing certain types of behaviors.

A discussion follows of William Latham’s and Stephen Todd’s proposal of using evolution not as an optimization tool, but as a tool with which artists and practitioners from other fields could breed potential solutions to the problems they deal with, based on some not explicitly defined criteria. An idea which proved to be a great inspiration for my PhD research topic.

Finally three architecture and design examples are there: Rogers, Stirk, Mabour and Partners collaboration with Expedition Engineering on The canopy in of a metro station in Naples. Sean Hanna’s and dr. Sivash S. Mahdavi’s research into optimization of the “SLS microstructure” and Morphogenetic Experiment 2 by Achim Menges and MiT’s Emergent Design Group:

This was confirmed by more than 300 sessions with the configurators, which took place during last three weeks. Parametric configurators with 4 and 18 customizable parameters (4P and 18P) where more popular than their genetic algorithms counterparts (4GA and 18GA), but genetic algorithm was a much more popular mean of driving the 37th parameters definition (37GA turned out to be more popular than 37P). I’m currently writing these findings up into a paper and some further, more in-depth analysis of the results will follow.

For the next iteration of the experiment, Federico Weber has generously offered to share his customizable table design with me. The work called Xylem is based on Voronoi diagram and will become a phenotype in Breeding Objects Experiment 2. Federico has already developed a parametric configurator for Xylem. It’s downloadable from here.

Breeding Objects Experiment 01 is my first experiment with configurators for mass customization of products over the Internet, conducted as part of PhD research at the Bartlett School of Graduate Studies. The experiment is a comparison of two types of configurators: “parametric” configurators and genetic algorithms configurators. In parametric configurators users have to specify the values of each of the parameters explicitly, while in genetic algorithms configurators they are not required to do so. Thanks to artificial selection, they can instead navigate through solution space by breeding objects, that is manually selecting parents of next generations.

The experiment is only about the patterns of interaction with the tools available, so you will not be asked to fill in any questionnaires. Once you start interaction with the tools, you will be able to navigate between them using links on top of each page.

Evolve rings where commissioned and are distributed by Fluid Forms. I have co-designed them together with Krystian Kwiecinski and they are available for purchase since today. They where designed with an aid of an artificial selection in genetic algorithm (GA). I have developed the phenotype together with Krystian and then wrote a purpose-built GA tool for breeding, rather than designing products in Processing. We will convert the GA tool into a configurator for mass customization of the rings. It should become available on Fluid Forms site early in 2010. Below is an explanation of the roots of evolutionary approach in design, which I wrote for the purpose of the launch.

Roots of the Evolve ring generative design process

Today Darwinian model of evolution by natural selection is widely acknowledged. It assumes that a new generation of individuals within a given specie inherits properties of these individuals from the previous generation, which where the most fit to survive. Fitness to survival is always evaluated within a given environment. It is not objective, but a subject to particular conditions which the individual happened to find itself in.

On a metaphorical level, theorists has refereed to evolution of culture, societies and products that they develop. Philip Steadman’s “The Evolution of Designs” from 1979 is a great roadmap of evolutionary metaphor in reference to any kind of artifacts, including designer objects and architecture. Bashford Dean’s study of historical evolution of helmet design or Lane-Fox’s and Pitt-Rivers’ tracing of evolutionary relationships of Australian weapons are just some of the examples discussed in Steadman’s influential book.

With the dawn of computing, evolution could become an applied tool used for seeking answers to particular problems rather than a conceptual model only. Survival of the fittest has been a source of inspiration for developers of “evolutionary algorithms”, which enable navigation through vast spaces of potential solutions in any imaginable field from marketing to transportation. They also help find solutions which are a best fit for given criteria, even if these are very complex and somewhat contradictory. The art world was quick to adapt the notion of evolution and survival of the fittest, but engineering was as well. In the art world William Latham imagined artists growing artworks rather than creating them already in 1985.

Later his renowned collaboration with IBM’s Stephen Todd led to development of the software called “Mutator”. The software literally enabled Latham to breed his sculptures just like the gardener breeds plants. In this case the individual most fit to survive is the one the artist likes the most. The possibility of breeding jewelry is also mentioned in Latham’s and Todd’s contribution to Evolutionary Design by Computers edited by Peter Bentley.

This is in contrast to application of evolution in engineering, where aesthetics do not have a significant impact on the validity of the solution. What is important in this case is performance. An example is the work of dr Peter Bentley and Stephen Manos on optimization of Holey optical fibres. These fibres are able to transmit light on large distances and their capacities are greatly enhanced by small air holes running through their entire length. Question was what shape, size and number of the wholes provides a fibre with best transmission capacity? Looking for an answer with evolutionary computation likely took millions of solutions to develop, but as the process was automated the time lapse was not so big and the results where rewarding.

Evolve ring brings evolution to the design world, not as a metaphor, but as a design tool. In design, aesthetics plays a crucial role, but the design has to be valid from a manufacturing stand point as well. This is why an algorithm used by Michal Piasecki and Krystian Kwiecinski is an amalgam of the GA from the art world and from the engineering world. Michal and Krystian developed a parametric phenotype first. Later Michal unleashed the process of evolution of jewelry and guided it towards the designs, which became the Evolve rings designer’s series from Fluid Forms. These pieces are breed, not designed.

John Frazer’s “An Evolutionary Architecture” from 1995 is an obligatory read for anyone interested in the amalgam of evolutionary computation and design. In other words anyone interested in the potential of “breeding designs” using evolutionary algorithms (genetic algorithms belong to this category). I was very happy to see it available online for free from the AA website.