Bio-inspiration: Learning Creative Design Principia

  • Tomasz Arciszewski
  • Joanna Cornell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4200)


Reusing or modifying known design concepts cannot meet new challenges facing engineering systems. However, engineers can find inspiration outside their traditional domains in order to develop novel design concepts. The key to progress and knowledge acquisition is found in inspiration from diverse domains.

This paper explores abstract knowledge acquisition for use in conceptual design. This is accomplished by considering body armor in nature and that developed in Europe in the last Millennium. The research is conducted in the context of evolution patterns of the Directed Evolution Method, which is briefly described. The focus is on conceptual inspiration. Analysis results of historic and natural body armor evolution are described and two sets of acquired creative design principia from both domains are presented. These principia can be used to stimulate human development of novel design concepts. Creative design principia, combined with human creativity, may lead to revolutionarychanges, rather than merely evolutionarysteps, in the evolution of engineering systems.


Design Concept Knowledge Acquisition Design Domain Direct Evolution Human Armor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Altshuller, G.S.: Creativity as an Exact Science. Gordon & Breach, New York (1988)Google Scholar
  2. 2.
    Arciszewski, T., Zlotin, B.: Ideation/Triz: Innovation Key To Competitive Advantage and Growth (1998), Internet:
  3. 3.
    Terninko, J., Zusman, A., Zlotin, B.: Systematic Innovation, An Introduction to TRIZ. St. Lucie Press (1998)Google Scholar
  4. 4.
    Clarke, D.: TRIZ: Through the Eyes of an American TRIZ Specialist, Ideation (1997)Google Scholar
  5. 5.
    Gero, J.: Computational Models of Innovative and Creative Design Processes, special double issue. Innovation: the key to Progress in Technology and Society. Arciszewski, T. (Guest Editor), Journal of Technological Forecasting and Social Change 64(2&3), 183–196 (2000)Google Scholar
  6. 6.
    Kicinger, R., Arciszewski, T., De Jong, K.A.: Evolutionary Computation and Structural Design: a Survey of the State of the Art. Int. J. Computers and Structures 83, 1943–1978 (2005)CrossRefGoogle Scholar
  7. 7.
    Lumsdaine, E., Lumsdaine, M.: Creative Problem Solving: Thinking Skills for a Changing World. McGraw-Hill, New York (1995)Google Scholar
  8. 8.
    Gordon, W.J.J.: Synectics, The Development of Creative Capacity (1961)Google Scholar
  9. 9.
    Arciszewski, T., Rossman, L. (eds.): Knowledge Acquisition in Civil Engineering. The ASCE (1992)Google Scholar
  10. 10.
    Clarke, D.W.: Strategically Evolving the Future: Directed Evolution and Technological Systems Development. Arciszewski, T. (ed.) Int. J. Technological Forecasting and Social Change, Special Issue: Innovation: The Key to Progress in Technology and Society 62(2&3), 133–154 (2000)Google Scholar
  11. 11.
    Zlotin, B., Zusman, A.: Directed Evolution: Philosphy, Theory and Practice, Ideation International (2005)Google Scholar
  12. 12.
    Bruet, B.J.F., Oi, H., Panas, R., Tai, K., Frick, L., Boyce, M.C., Ortiz, C.: Nanoscale morphology and indentation of individual nacre tablets from the gastropod mollusc Trochus niloticus. J. Mater. Res. 20(9), 2400–2419 (2005), Information about lab: Google Scholar
  13. 13.
    Arciszewski, T., Uduma, K.: Shaping of Spherical Joints in Space Structures. Int. J. Space Structures 3(3), 171–182 (1988)Google Scholar
  14. 14.
    Vogel, S.: Cats’ Paws and Catapults. W.W. Norton & Company, New York (1998)Google Scholar
  15. 15.
    Arciszewski, T., Kicinger, R.: Structural Design inspired by Nature. In: Topping, B.H.V. (ed.) Innovation in Civil and Structural Engineering Computing, pp. 25–48. Saxe-Coburg Publications, Stirling (2005)CrossRefGoogle Scholar
  16. 16.
    Balgooyen, T.G.: Evasive mimicry involving a butterfly model and grasshopper mimic. The American Midland Naturalist 137(1), 183 (1997)CrossRefGoogle Scholar
  17. 17.
    Wickler, W.: Mimicry in plants and animals (Translated by R.D. Martin from the German edition), p. 255. World Univ. Library, London (1968)Google Scholar
  18. 18.
    D’Arcy, T.: On Growth and Form: The Complete Revised Edition. Dover Publications, Mineola (1992)Google Scholar
  19. 19.
    Goel, A.K., Bhatta, S.R.: Use of design patterns in analogy based design. Advanced Engineering Informatics 18(2), 85–94 (2004)CrossRefGoogle Scholar
  20. 20.
    De Jong, K.: Evolutionary computation: a unified approach. MIT Press, Cambridge (2006)MATHGoogle Scholar
  21. 21.
    Wolfram, S.: New Kind of Science, vol. Il. Wolfram Media, Champaign (2002)MATHGoogle Scholar
  22. 22.
    Goldberg, D.E.: Computer-aided gas pipeline operation using genetic algorithms and rule learning, Part I: genetic algorithms in pipeline optimization. Engineering with Computers, 47–58 (1987)Google Scholar
  23. 23.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Pub. Co., Reading (1989)MATHGoogle Scholar
  24. 24.
    Murawski, K., Arciszewski, T., De Jong, K.: Evolutionary Computation in Structural Design. Int. J. Engineering with Computers 16, 275–286 (2000)MATHCrossRefGoogle Scholar
  25. 25.
    Kicinger, R., Arciszewski, T., De Jong, K.A.: Evolutionary Designing of Steel Structures in Tall Buildings. ASCE J. Computing in Civil Engineering 19(3), 223–238 (2005)CrossRefGoogle Scholar
  26. 26.
    Koza, R.J.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)MATHGoogle Scholar
  27. 27.
    Koza, J.R., Bennett III, F.H., Andre, D., Keane, M.A.: Genetic Programming: Biologically Inspired Computation that Creatively Solves. MIT Press, Cambridge (2001)Google Scholar
  28. 28.
    Ishino, Y., Jin, Y.: Estimate design intent: a multiple genetic programming and multivariate analysis based approach. Advanced Engineering Informatics 16(2), 107–126 (2002)CrossRefGoogle Scholar
  29. 29.
    Kicinger, R.: Emergent Engineering Design: Design Creativity and Optimality Inspired by Nature, Ph.D. dissertation, Information Technology and Engineering School, George Mason University (2004)Google Scholar
  30. 30.
    Kicinger, R., Arciszewski, T., De Jong, K.A.: Generative Representations in Structural Engineering. In: Proceedings of the 2005 ASCE International Conference on Computing in Civil Engineering, Cancun, Mexico (July 2005)Google Scholar
  31. 31.
    Arciszewski, T., De Jong, K.: Evolutionary Computation in Civil Engineering: Research Frontiers. In: Topping, B.H.V. (ed.) Civil and Structural Engineering Computing, pp. 161–185 (2001)Google Scholar
  32. 32.
    Zlotin, B., Zusman, A.: Tools of Classical TRIZ, Ideation International, p. 266 (1999)Google Scholar
  33. 33.
    Eugene, S., Gaffney, J., Hutchison, H., Farish, A., Lorraine, J., Meeker, L.: Modern turtle origins: the oldest known cryptodire. Science 237, 289 (1987)CrossRefGoogle Scholar
  34. 34.
    Pennisi, E.: Changing a fish’s bony armor in the wink of a gene: genetic researchers have become fascinated by the threespine stickleback, a fish that has evolved rapidly along similar lines in distant lakes. Science 304(5678), 1736 (2004)CrossRefGoogle Scholar
  35. 35.
    McPhail, J., Lindsey, C.: Freshwater fishes of northwestern Canada and Alaska. Bulletin of the Fisheries Research Board of Canada 173, 1–381 (1970)Google Scholar
  36. 36.
    Bell, M.: Evolution of phenotypic diversity in Gasterosteus aculeatus superspecies on the Pacific Coast of North America. Systematic Zoology 25, 211–227 (1976)CrossRefGoogle Scholar
  37. 37.
    Bell, M., Foster, S.: Introduction to the evolutionary biology of the threespring stickle-back. In: Bell, M.A., Foster, S.A. (eds.) The evolutionary biology of the three spine stickleback, pp. 1–27. Oxford University Press, Oxford (1993)Google Scholar
  38. 38.
    Bell, M., Orti, G., Walker, J., Koenings, J.: Evolution of pelvic reduction in threespine stickleback fish: a comparison of competing hypotheses. Evolution 3(47), 906–914 (1993)CrossRefGoogle Scholar
  39. 39.
    Storrs, E.: The Astonishing Armadillo. National Geographic 161(6), 820–830 (1982)Google Scholar
  40. 40.
    Fox, D.L.: Dasypus novemcinctus: Nine-Banded Armadillo (January 18, 1996) (November 3, 1999),
  41. 41.
    Myers, P.: Dasypodidae (Online), Animal Diversity Web (accessed February 08, 2006), at:
  42. 42.
    Breece, G., Dusi, J.: Food habits and home range of the common long-nosed armadillo Dasypus novemcinctus in Alabama. In: Montgomery, G.G. (ed.) The evolution and ecology of armadillos, sloths and vermilinguas, pp. 419–427. Smithsonian Institution Press, Washington (1985)Google Scholar
  43. 43.
    Stuart, A.: Who (or what) killed the giant armadillo? New Scientist 17, 29 (1986)Google Scholar
  44. 44.
    Savage, R.J.G., Long, M.R.: Mammal Evolution, an Illustrated Guide, p. 259. Facts of File Publications, New York (1986)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tomasz Arciszewski
    • 1
  • Joanna Cornell
    • 1
  1. 1.George Mason UniversityFairfaxUSA

Personalised recommendations