Wednesday, June 1, 2011

Towards Grammars for Cradle-to-Cradle Design (Doug Fisher & Mary Lou Maher)

Cradle-to-cradle (C2C) design (McDonough & Braungart, 2002) recognizes that nothing short of full recycling of materials with no degradation in material quality is necessary for long-term planet sustainability. C2C advocates looking to the natural world as an ideal model of recycling, where organic materials are continually recycled through processes of decay and growth. They propose design methodology that separates biological cycles and synthetic-material cycles, enabling biological material to be reclaimed through natural processes without synthetic and toxic residue, and enabling the full reuse of synthetic material through technological processes so as to eliminate resource depletion and toxic poisoning. While domain specialists define and elaborate these interacting cycles of materialuse, there are ample opportunities for Artificial Intelligence techniques to manage the complexities and articulate C2C design processes.

C2C goals suggest the necessity of holistic approaches that design the cycling of material, and include attention to the energy required to maintain the cycles. Reuse of material from one product line can be cycled back to the same product line or another product line. In reality, this already happens through normal recycling (e.g., plastic bottles are recycled into park benches), but the sources and targets of recycling are typically identified after major design decisions, leading to inefficiencies, material loss, and degradation. By designing C2C product families, reuse cycles can be made more efficient, with known and predictable trajectories for reused material. The figure illustrates that while there may be materials that come from outside a family and there are materials that are byproducts of the family production, a family design would seek to minimize these and to exploit them in a still larger context. That is, product families are dense subgraphs within a larger network.

Since grammars have been used extensively to model design processes, we are considering grammars to model C2C design of products and product families; productions of a grammar can represent operators for composing objects, as well as operators for decomposing objects (e.g., for purposes of recycling). We are defining classes of grammars that are aligned with C2C design desiderata. For example, a class of reversible designs may be represented by augmented grammars that limit artifacts to those that can be decomposed into basic parts with energy that is no greater than the energy required to compose the artifact initially; an example of an artifact that is not reversible might be a leather shoe that is tanned with a toxic tanner – the energy required to apply the tanner may be trivial, but the energy required to separate the tanner from leather at the shoe’s end of life may be horrendous.

Grammars, heuristic search and various forms of machine learning are highlighted as critical in grappling with the complexities of C2C design under many tradeoffs and constraints involving material and energy.

A preprint of the paper can be found at:

The presentation can be found at

Friday, April 22, 2011

What can AI offer to Biologically Inspired Sustainable Design?

Computational sustainability is becoming big in artificial intelligence (AI) research. For the first time ever, this year AAAI is organizing a special track on computational sustainability as part of its annual National Conference on AI <>. In addition, this year AAAI held a spring symposium on AI and sustainable design <> organized by Douglas Fisher (Vanderbilt Univerity) and Mary Lou Maher (University of Maryland at College Park) - see the first blog here for their summarization of the sympsosium. The symposium was preceded by an NSF workshop on computational methods and tools for biologically inspired design <>. I had the pleasure of co-chairing the NSF workshop on biologically inspired design with Daniel McAdams (Texas A&M University) and Robert Stone (Oregon State University), participated in the spring symposium on AI and sustainable design, and am looking forward to the AAAI track on computational sustainability. All these promising initiatives raise the question of scientific linkage to me: What, for example, is the scientific link between AI and biologically inspired design, between AI, biologically inspired design and sustainable design, and between AI, sustainable design and computational sustainability?

Let us take these questions one at a time. Biologically inspired design, also known as biomimicry or bionics, is a growing movement in design that espouses the use of nature as an analogue for generating ideas for designing technology. Think, for example, about the design of new iridescent computer screen display technologies based on the nanostructures on the wings of morpho butterflies. While biologically inspired design is growing as a design movement, its practice remains ad hoc, with little systematization of biological knowledge from a design perspective or the design process itself. This is where AI can help -- helping to answer a myriad of questions: What might be a good ontology for representing knowledge of biological systems? What might be a good ontology for representing problems of technological design? How might biological knowledge relevant to a design problem be accessed? How might design patterns be learned from specific biological analogues? What might be the process of analogical transfer of biological knowledge to design of technology? How might a design concept be evaluated? And so on. Thus, AI offers process, content and representation techniques of problem solving, memory and learning to help transform biologically inspired design from a promising paradigm into a principled methodology.

What about the relationship between AI, biologically inspired design and sustainable design? First, note that while biologically inspired design is a method, sustainable design is a problem. That is, one can potentially use the method of biologically inspired design to address a problem in sustainable design. Second, note also that not all designs generated through biologically inspired design are necessarily sustainable. The design of a robot that can walk on water mimicking the locomotion of the basilisk lizard has little to do with sustainability. However, the design of blades in windmill turbines based on the tubercles on the fins of humpback whales is clearly driven by a problem in sustainable design. But note that the transfer of the design of tubercles requires a deep understanding of their functional role in maximizing energy efficiency. Thus, if we can understand the principles of biological designs – the principles that make them energy efficient, for example – then biologically inspired design could be an important method for addressing problems of sustainable design. It follows that by helping systematize biological knowledge and biologically inspired design, AI can also help address problems in sustainable design. (See the paper [1] my colleagues and I wrote for the AAAI Symposium on AI and Sustainable Design for more details.)

Finally, let us look at the relationship between AI, sustainable design and computational sustainability. The AAAI Call for Papers for the special track on computational sustainability invites papers on sensing, modeling, analysis, prediction, control and optimization of complex systems relevant to sustainability <>. This is an important agenda. AI research on sustainable design, in addition, holds the promise of new kinds of complex system designs such as biologically inspired sustainable designs. AI research on sustainable design also entails designs of actions, plans, behaviors, processes and policies pertaining to sustainability. I call upon AAAI to explicitly include sustainable design in next year’s special track on computational sustainability.


[1] Ashok Goel, Bert Bras, Michael Helms, Spencer Rugaber, Craig Tovey, Swaroop Vattam, Marc Weissburg, Bryan Wiltgen, & Jeannette Yen. Design Patterns and Cross-Domain Analogies in Biologically Inspired Sustainable Design. In Proc. AAAI Spring Symposium on AI and Sustainable Design, Stanford University, Palo Alto, March 2011, pp. 45-51.


An earlier version of this entry appears in the Computing Community Consortium blog.

Tuesday, April 19, 2011

The Tao of Sustainability: Sustainable Design in a Globalization Context

An International Conference on Sustainable Design in a Globalization Context
27-29 October 2011

Academy of Arts and Design, Tsinghua University, Beijing

Academy of Arts and Design, Tsinghua University, Beijing
School of Art and Design, Aalto University, Helsinki (formerly University of Art and Design Helsinki)

This conference explores the possibilities of design in developing sustainable solutions for the future of mankind.

The constantly accelerating globalization with its rapidly growing flow of artefacts and consumption is a burden not only to the natural environment but to civilizations, communities and individuals. The deepening ecological crisis is a call also for design: in which ways can it help in solving problems of sustainability in the prevailing context of globalization?

Design as a reflection of the development of human civilization and as a powerful catalyst to social, economic and cultural developments, is also confronted with the opportunities and challenges brought by these current megatrends.

Sustainable Design Strategies in a Global Context

- the direction and strategies of design in a global context
- social innovation and sustainable design
- culture and sustainable design
- pedagogy in sustainable design education
- methodologies of sustainable design
- service design/sustainability
- business aspect of sustainable design
- sustainable living environment


All inquiries to this address:

Friday, April 15, 2011

Why Artificial Intelligence and Sustainable Design?

Long-term environmental and societal sustainability requires that artifacts, materials, systems and processes be designed to minimize energy and waste and to maximize reuse and utility; we should hope that the days of designing things that are ultimately thrown away are rapidly coming to an end. The ‘design for X’ paradigm considers downstream objectives, such as reusability, early in the design process. Designers are being challenged to consider factors that had been previously given little attention, like life cycle costs along many dimensions; including energy requirements during manufacture, use and end-of-use phases, and material loss and environmental damage at the end of a product’s life. A vision for sustainable design is cradle-to-cradle design (McDonough and Braungart, 2002), in which products are designed and built in ways that enable full reuse at low costs (e.g., energy), with nothing thrown out and nothing degraded. Our motivation to organize the symposium stemmed from our presumption that the increased complexity of design necessitated by a desire for very long-term planet sustainability requires application of and advances in artificial intelligence.

This blog is a continuing discussion that started at the AAAI Spring Symposium on Artificial Intelligence and Sustainable Design at Stanford University from March 21-23, 2011. The symposium focussed on domains, problems and challenges of sustainable design and the role that AI can play in sustainable design.

The symposium brought together researchers from three primary areas:
• AI and Design
• Computational Sustainability
• Design for Sustainability
AI and design is an established field already, with conferences and journals; AI has provided computational approaches to design processes and the representation of design knowledge. Design for sustainability is not so much a field as it is a set of principles, which are implemented on an ad hoc basis. Computational sustainability is a nascent field, but already influential in moving AI and other computational fields into addressing sustainability questions.

About 25-30 people physically attended the symposium. There was also a virtual participation option, which was made available to co-authors, colleagues, and students of the authors of the papers as a way of broadening participation without requiring additional travel — and as a result about 10 avatars attended in Second Life at various times. A total of 18 papers were presented over the course of the two-and-a-half days. Presentation topics included smart buildings, environmentally smart occupants, decision support systems to support energy analyses, optimization to inform design decision making, and theoretical models of cradle-to-cradle design.

The symposium included two invited talks. Alice Agogino (University of California, Berkeley, Department of Mechanical Engineering) described the Smart Lighting project – a wireless sensor network for customizable commercial lighting control. This application requires decision making in the face of uncertainty, with needs for system self-configuration and learning. Kirstin Gail (Autodesk) spoke on Bloom, a recyclable laptop developed by graduate students of a Stanford University course on design innovation; Bloom represents a new class of electronic products that can be easily disassembled for recycling by the consumer at end of product life. In both of these talks, the speakers noted that sustainability was only achievable by considering human behavior as a significant factor. In fact, this recognition of the importance of social influences and implications of human behavior was an overarching theme of the symposium generally.

There were several major sustainability themes in the papers and discussions, including energy conservation, material recycling, lifecycle and environmental impact analysis. The AI and computational themes included approaches to modeling sustainable design knowledge and processes, sustainability through computational support for biologically inspired design, characterizing and managing uncertainty, machine learning and case-based reasoning for sustainable design, and computational tools for estimating sustainability costs in design alternatives.

Participants also engaged in three separate breakout groups to brainstorm on forward-thinking research directions at the intersection of AI and sustainable design. Many themes were discussed, including (1) the role of AI in modeling the effect of human behavior on sustainable design of artifacts and systems; (2) the role of AI in biologically inspired sustainable design, and (3) the role of customization in fitting designs to individuals and groups in a manner that improves sustainability indices.

The Symposium was successful in achieving a common interest among the participants, which we hope will be maintained through a continued effort to communicate and share research on this topic. Our expectation is that AI will provide formal models, languages and methods of sustainable design, thus helping to push sustainable design from the status of interest area into the status of a discipline.

Douglas Fisher and Mary Lou Maher were co-chairs of this symposium. The papers of the symposium were published as AAAI Press Technical Report SS-11-01.

Douglas Fisher is an associate professor at Department of Electrical Engineering and Computer Science, Vanderbilt University.

Mary Lou Maher is a senior research scientist at the Human-Computer Interaction Lab, University of Maryland.

Reference: McDonough, W. and Braungart, M. (2002) Cradle To Cradle: Remaking The Way We Make Things, North Point Press, 2002.