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A content account of creative analogies in biologically inspired design

Published online by Cambridge University Press:  25 October 2010

Swaroop S. Vattam ,
Michael E. Helms  and
Ashok K. Goel
Swaroop S. Vattam
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing and Center for Biologically Inspired Design, Georgia Institute of Technology, Atlanta, Georgia, USA
Michael E. Helms
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing and Center for Biologically Inspired Design, Georgia Institute of Technology, Atlanta, Georgia, USA
Ashok K. Goel
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing and Center for Biologically Inspired Design, Georgia Institute of Technology, Atlanta, Georgia, USA
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Abstract

The growing movement of biologically inspired design is driven in part by the need for sustainable development and in part by the recognition that nature could be a source of innovation. Biologically inspired design by definition entails cross-domain analogies from biological systems to problems in engineering and other design domains. However, the practice of biologically inspired design at present typically is ad hoc, with little systemization of either biological knowledge for the purposes of engineering design or the processes of transferring knowledge of biological designs to engineering problems. In this paper we present an intricate episode of biologically inspired engineering design that unfolded over an extended period of time. We then analyze our observations in terms of why, what, how, and when questions of analogy. This analysis contributes toward a content theory of creative analogies in the context of biologically inspired design.

Keywords

AnalogyBiologically Inspired DesignBiomimetic DesignCreativityInnovation
Type
Special Issue Articles
Information
AI EDAM , Volume 24 , Issue 4: Biologically Inspired Design , November 2010 , pp. 467 - 481
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

Anderson, J.R., & Thompson, R. (1989). Use of analogy in a production system architecture. In Similarity and Analogical Reasoning (Vosniadou, S., & Ortony, A., Eds.), pp. 267–297. London: Cambridge University Press.CrossRefGoogle Scholar
Barber, J., Bhatta, S., Goel, A., Jacobson, M., Pearce, M., Penberthy, L., Shankar, M., Simpson, R., & Stroulia, E. (1992). AskJef: integration of case-based and multimedia technologies for interface design support. In Artificial Intelligence in Design '92 (Gero, J.S., Ed.), pp. 457–474. Dordrecht: Kluwer.Google Scholar
Bar-Cohen, Y., Ed. (2006). Biomimetics: Biologically Inspired Technologies. New York: Taylor & Francis.Google Scholar
Benyus, J. (1997). Biomimicry: Innovation Inspired by Nature. New York: William Morrow.Google Scholar
Bhatta, S., & Goel, A.K. (1997). A functional theory of design patterns. Proc. 15th Int. Joint Conf. Artificial Intelligence (IJCAI-97), pp. 294–300, Nagoya, Japan.Google Scholar
Biomimicry Institute. (2008). Ask Nature—The Biomimicry Design Portal. Accessed at http://www.asknature.org/Google Scholar
Boden, M.A. (1994). What is creativity? In Dimensions of Creativity (Boden, M.A., Ed.), pp. 75–117. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Bonnardel, N. (2000). Towards understanding and supporting creativity in design: analogies in a constrained cognitive environment. Knowledge-Based Systems 13, 505–513.CrossRefGoogle Scholar
Bonser, R., & Vincent, J. (2007). Technology trajectories, innovation, and the growth of biomimetics. Journal of Mechanical Engineering Science 221(10), 1177–1180.CrossRefGoogle Scholar
Cagan, J., & Vogel, C. (2002). Creating Breakthrough Products. Innovation From Product Planning to Program Approval. Upper Saddle River, NJ: Prentice–Hall.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B. (2005). A functional representation for aiding biomimetic and artificial inspiration of new ideas. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19(1), 113–132.CrossRefGoogle Scholar
Chandrasekaran, B. (1990). Design problem solving: a task analysis. AI Magazine 1990(1), 59–71.Google Scholar
Chiu, I., & Shu, L. (2007). Biomimetic design through natural language analysis to facilitate cross-domain analysis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21(1), 45–59.CrossRefGoogle Scholar
Christensen, B., & Schunn, C. (2008). The relationship of analogical distance to analogical function and preinventive structure: the case of engineering design. Memory & Cognition 35(1), 29–38.CrossRefGoogle Scholar
Clement, J. (1988). Observed methods for generating analogies in scientific problem solving. Cognitive Science 12, 563–586.CrossRefGoogle Scholar
Clement, J. (2008). Creative Model Construction in Scientists and Students: The Role of Imagery, Analogy, and Mental Simulation. Dordrecht: Springer.CrossRefGoogle Scholar
Darden, L. (1983). Artificial intelligence and philosophy of science. Philosophy of Science Association 2, 147–165.Google Scholar
Dunbar, K. (1995). How scientists really reason: scientific reasoning in real-world laboratories. In Mechanisms of Insight (Sternberg, R.J., & Davidson, J., Eds.), pp. 365–395. Cambridge, MA: MIT Press.Google Scholar
Dunbar, K. (2001). The analogical paradox. In The Analogical Mind: Perspectives From Cognitive Science (Gentner, D., Holyoak, K.J., & Kokinov, B.N., Eds.). Cambridge, MA: MIT Press.Google Scholar
Falkenhainer, B., Forbus, K., & Gentner, D. (1989). The structure-mapping engine: algorithms and examples. Artificial Intelligence 41(1), 63.Google Scholar
Finger, S., & Dixon, J. (1989). A review of research in mechanical engineering design. Part 1: descriptive, prescriptive and computer-based models of design processes. Representations, analysis, and design for the life cycle. Research in Engineering Design 1, 51–67.CrossRefGoogle Scholar
Gebhardt, F., Voß, A., Gräther, W., & Schmidt-Belz, B. (1997). Reasoning With Complex Cases. Norwell, MA: Kluwer.CrossRefGoogle Scholar
Gentner, D. (1983). Structure-mapping: a theoretical framework for analogy. Cognitive Science 7, 155–170.Google Scholar
Gick, M., & Holyoak, K.J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15(1), 1–38.CrossRefGoogle Scholar
Goel, A., & Bhatta, S. (2004). Use of design patterns in analogy-based design. Advanced Engineering Informatics 18(2), 85–94.CrossRefGoogle Scholar
Goel, A., & Chandrasekaran, B. (1988). Integrating case-based and model-based reasoning for design problem solving. Proc. AAAI-88 Workshop on AI in Design, Minneapolis, MN.Google Scholar
Goel, A., & Chandrasekaran, B. (1992). Case-based design: a task analysis. In Artificial Intelligence Approaches to Engineering Design: Innovative Design (Tong, C., & Sriram, D., Eds.), Vol. 2, pp. 165–184. San Diego, CA: Academic Press.CrossRefGoogle Scholar
Goel, A., & Craw, S. (2005). Design, innovation and case-based reasoning. Knowledge Engineering Review 20(3), 271–276.CrossRefGoogle Scholar
Goel, A., Gomez, A., Grue, N., Murdock, M., Recker, M., & Govindaraj, T. (1996). Explanatory interfaces in interactive design environments. Proc. 4th Int. Conf. AI in Design (Gero, J., & Sudweeks, F., Eds.), pp. 1–20. Boston: Kluwer Academic.Google Scholar
Goel, A.K. (1997). Design, analogy, and creativity. IEEE Expert 12(3), 62–70.CrossRefGoogle Scholar
Griffith, T., Nersessian, N., & Goel, A. (1996). The role of generic models in conceptual change. Proc. 18th Cognitive Science Conf., San Diego, CA, July.Google Scholar
Griffith, T., Nersessian, N., & Goel, A. (2000). Function-follows-form: generative modeling in scientific reasoning. Proc. 22nd Cognitive Science Conf.Google Scholar
Helms, M., Vattam, S., & Goel, A. (2009). Biologically inspired design: process and products. Design Studies 30(5), 606–622.CrossRefGoogle Scholar
Hofstadter, D. (1979). Godel, Escher, Bach: An Eternal Golden Braid. New York: Basic Books.Google Scholar
Hofstadter, D. (1996). Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought. New York: Basic Books.Google Scholar
Hofstadter, D., & Mitchell, M. (1996). The copycat project. In Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought, pp. 31–112. New York: Basic Books.Google Scholar
Holyoak, K.J., & Thagard, P. (1989). Analogical retrieval by constraint satisfaction. Cognitive Science 13, 295–355.CrossRefGoogle Scholar
Hua, K., Faltings, B., & Smith, I. (1996). CADRE: case-based geometric design. Artificial Intelligence in Engineering 10(2), 171–183.CrossRefGoogle Scholar
Kedar-Cabelli, S. (1985). Purpose-directed analogy. Proc. 7th Annual Conf. Cognitive Science Society, Mahwah, NJ: Erlbaum.Google Scholar
Kokinov, B. (1998). Analogy is like cognition: dynamic, emergent, and context-sensitive In Advances in Analogy Research: Integration of Theory and Data From the Cognitive, Computational, and Neural Sciences (Holyoak, K., Gentner, D., & Kokinov, B., Eds.), pp. 96–105. Sofia, Bulgaria: New Bulgarian University.Google Scholar
Kruger, C., & Cross, N. (2006). Solution-driven vs. problem-driven design: strategies and outcomes. Design Studies 27(5), 527–548.CrossRefGoogle Scholar
Linsey, J., Wood, K., & Markman, A. (2008). Modality and representation in analogy. Artificial Intelligence for Engineering, Design, Analysis and Manufacturing 22(2), 85–100.CrossRefGoogle Scholar
Maher, M., Balachandran, M., & Zhang, D. (1995). Case-Based Reasoning in Design. Mahwah, NJ: Erlbaum.Google Scholar
Maher, M.L., & Pu, P. (1997). Issues and Applications of Case-Based Reasoning in Design. Mahwah, NJ: Erlbaum.Google Scholar
Mak, T., & Shu, L. (2008). Using descriptions of biological phenomena for idea generation. Research in Engineering Design 19(1), 21–28.CrossRefGoogle Scholar
Nagle, R., Midha, P., Tinsley, A., Stone, R., McAdams, D., & Shu, L. (2008). Exploring the use of functional models in biomimetic concept design. ASME Journal of Mechanical Design 130(12), 121102–121114.CrossRefGoogle Scholar
Nersessian, N.J. (1992). How do scientists think? Capturing the dynamics of conceptual change in science. In Cognitive Models of Science (Giere, R.N., Ed.), pp. 3–45. Minneapolis, MN: University of Minnesota Press.Google Scholar
Nersessian, N.J. (1999). Model-based reasoning in conceptual change. In Model-Based Reasoning in Scientific Discovery (Magnani, L., Nersessian, N.J., & Thagard, P., Eds.), pp. 5–22. New York: Kluwer Academic/Plenum.CrossRefGoogle Scholar
Nersessian, N.J. (2008). Creating Scientific Concepts. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Pahl, G., & Beitz, W. (1996). Engineering Design: A Systematic Approach (Wallace, K., Trans.), 2nd ed.Berlin: Springer.CrossRefGoogle Scholar
Pearce, M., Goel, A., Kolodner, J., Zimring, C., Sentosa, L., & Billington, R. (1992). Case-based decision support: a case study in architectural design. IEEE Expert 7(5), 14–20.CrossRefGoogle Scholar
Polya, G. (1954). Mathematics and Plausible Reasoning. Princeton, NJ: Princeton University Press.Google Scholar
Popper, K., Merson, R.L., & Camirand, W.M. (1968). Desalination by osmosis–reverse osmosis couple. Science 159(821), 1364–1365.CrossRefGoogle ScholarPubMed
Sarkar, P., & Chakrabarti, A. (2008). The effect of representation of triggers on design outcomes. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 22(2), 101–116.CrossRefGoogle Scholar
Smith, I., Lottaz, C., & Faltings, I. (1995). Spatial Composition Using Cases: IDIOM, pp. 88–97. LNCS Vol. 1010. New York: Springer.Google Scholar
Smyth, B., Keane, M., & Cunningham, P. (2001). Hierarchical case-based reasoning: integrating case-based and decompositional problem-solving techniques for plant-control software design. IEEE Transactions on Knowledge and Data Engineering 13(5), 793–812.CrossRefGoogle Scholar
Srinivasarao, M., & Padilla, L. (1997). Biologically inspired design: color on wings. Proc. Materials Research Society Symp., Pittsburgh, PA.Google Scholar
Suh, N.P. (1990). Principles of Design. New York: Oxford University Press.Google Scholar
Sycara, K., Guttal, R., Koning, J., Narasimhan, S., & Navinchandra, D. (1991). CADET: a case-based synthesis tool for engineering design. International Journal of Expert Systems 4(2), 157–188.Google Scholar
Vattam, S., Helms, M., & Goel, A. (2008). Compound analogical design: interaction between problem decomposition and analogical transfer in biologically inspired design. Proc. 3rd Int. Conf. Design Computing and Cognition, pp. 377–396. Berlin: Springer.CrossRefGoogle Scholar
Vattam, S., Helms, M., & Goel, A. (2009). Nature of creative analogies in biologically inspired innovative design. Proc. 7th ACM Conf. Creativity and Cognition, Berkeley, CA, October.Google Scholar
Vattam, S., Wiltgen, B., Helms, M., Goel, A., & Yen, J. (in press). DANE: fostering creativity in and through biologically inspired design. Proc. 1st Int. Conf. Design Creativity, Kobe, Japan, November 2010.Google Scholar
Vincent, J., & Mann, D. (2002). Systematic transfer from biology to engineering. Philosophical Transactions of the Royal Society of London 360, 159–173.CrossRefGoogle ScholarPubMed
Visser, W. (1996). Two functions of analogical reasoning in design: a cognitive-psychology approach. Design Studies 17, 417–434.CrossRefGoogle Scholar
Winston, P. (1980). Learning and reasoning by analogy. Communications of the CACM 23, 12.Google Scholar
Wills, L., & Kolodner, J. (1994 a). Towards more creative case-based design systems. Proc. AAAI-94, Seattle.Google Scholar
Wills, L., & Kolodner, J. (1994 b). Explaining serendipitous recognition in design. Proc. 16th Cognitive Science Conf., pp. 940–945. Mahwah, NJ: Erlbaum.Google Scholar
Yaner, P., & Goel, A. (2007). Understanding drawings by compositional analogy. Proc. Int. Joint Conf. Artificial Intelligence (IJCAI-2007), pp. 1131–1137.Google Scholar
Yaner, P., & Goel, A. (2008). From design drawings to structural models by compositional analogy. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 22(2), 117–128.CrossRefGoogle Scholar
Yen, J., & Weissburg, M. (2007). Perspectives on biologically inspired design: introduction to the collected contributions. Journal of Bioinspiration and Biomimetics 2, S170–S181.Google Scholar
Yen, J., Weissburg, M., Helms, M., & Goel, A. (in press). Biologically inspired design: a tool for interdisciplinary education. In Biomimetics: Nature-Based Innovation (Bar-Cohen, Y., Ed.). New York: Taylor & Francis.Google Scholar