Skip to main content

Abstract

The paper argues the point that thanks to a recent shift of emphasis from logic based to autonomous, rational and interactive models of intelligent behaviour, artificial intelligence can now support engineering design better than ever before. Logic, however, provides still the best means for representing design objects and knowledge about them. Design synthesis, especially if executed in a concurrent setting, can build upon agent technology Finally, the evolutionary approach to design is discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aha, D. and Daniels, J.J. (eds.); Case-Based Reasoning Integrations; Papers from the 1998 Workshop; Technical Report WS-98–15, AAAI Press, Menlo Park, CA.

    Google Scholar 

  2. Alting, L.; Legarth, J.B.; “Life cycle engineering and design”; Annals of the CIRP 44(2) pp. 569–580.

    Google Scholar 

  3. Back, T.; Hammel, U.; Schwefel, H.-P.; “Evolutionary computation: comments on the history and current state”; IEEE Transactions on Evolutionary Computation 1(1) pp. 3–17.

    Google Scholar 

  4. Bentley, P.J.; “Aspects of evolutionary design by computers”; In Bentley, P.J. (ed.), Evolutionary Design by Computers; Academic Press.

    Google Scholar 

  5. Chittaro, L.; Kumar, A.N.; Special issue on “Reasoning about function”; Artificial Intelligence in Engineering 12(4)

    Google Scholar 

  6. Culberson, J.C.; “On the futility of blind search: an algorithmic view of no free lunch”; Evolutionary Computation 6(2), pp. 109–127.

    Google Scholar 

  7. Cutkosky, M.R. et al.; “PACT: An experiment in integrated concurrent engineering systems”; Computer 26(1) pp. 28–37.

    Google Scholar 

  8. Darr, T.D.; Birmingham, W.P.; “Automated design for concurrent engineering”; IEEE Expert 9(5), pp. 35–42.

    Google Scholar 

  9. Davis, R.; “What are intelligence? And why?”; AI Magazine 19(1) pp. 91–110.

    Google Scholar 

  10. Dennett, D.C.; Darwin’s Dangerous Idea; Simon & Schuster.

    Google Scholar 

  11. Doyle, J. et al.; “Strategic directions in artificial intelligence”; ACM Computing Surveys 28(4) pp. 651–670.

    Google Scholar 

  12. Eaton, P.S.; Freuder, E.C.; Wallace, R.J.; “Constraints and agents: Confronting ignorance”; AI Magazine 19(2) pp. 51–65.

    Google Scholar 

  13. Eversheim, W. (ed.); Feature issue on “Models and methods for an integrated design of products and processes”; European Journal of Operational Research 100(2)

    Google Scholar 

  14. Faltings, B.; “A symbolic approach to qualitative kinematics”; Artificial Intelligence 56(2–3) pp. 139–170.

    Google Scholar 

  15. Faltings, B.; Freuder, E.C. (eds.); Special issue on “Configuration”; IEEE Intelligent Systems 13(4)

    Google Scholar 

  16. Fogel, D.B.; Evolutionary Computation: Toward a New Philosophy of Machine Intelligence; IEEE Press, Piscataway, NJ.

    Google Scholar 

  17. Gadh, R. (ed.); Special issue on “Computer-based collaborative design”; Computer-Aided Design 28(5)

    Google Scholar 

  18. Gelsey, A.; Schwabacher, M.; Smith, D.; “Using modeling knowl-edge to guide design space search”; Artificial Intelligence 101(1–2) pp.35–62. [Ginsberg, 1993] Ginsberg, M.; Essentials of Artificial Intelligence; Morgan Kaufmann, San Francisco, CA.

    Google Scholar 

  19. Goel, V.; Pirolli, P.; “The structure of design problem spaces”; Cognitive Science 16, pp. 395–429.

    Google Scholar 

  20. Horvath, M.; Markus, A.; Vancza, J.; “Conflicts in manufacturing systems - A problem setting”; In Yoshikawa, H.; Goossenaerts, J. (eds.); Design of Information Infrastructure Systems for Manufacturing; North-Holland, pp. 265–279.

    Google Scholar 

  21. van Hentenryck, P. et al.; “Strategic directions in constraint programming”; ACM Computing Survey 28(4) pp. 701–726.

    Google Scholar 

  22. Hower, W.; Rosenman, M. (eds.); Special issue on “Evolutionary systems in design”; Artificial Intelligence in Engineering 11(3) [Jansen and Krause, 1996] Jansen, H.; Krause, F.-L. (eds.); Life Cycle Modeling for Innovative Products and Processes; Chapman & Hall, London.

    Google Scholar 

  23. Joslin, D.E.; Clements, D.P.; “Squeaky wheel optimization”; In Proc. of the AAAI-98 Conf.; AAAI Press, pp. 340–346.

    Google Scholar 

  24. Kramer, G.A.; “A geometric constraint engine”; Artificial Intelligence 58(1–3) pp. 327–360.

    Google Scholar 

  25. Lenat, D.B.; “CYC: A large-scale investment in knowledge infrastructure”; Communications of the ACM 38(11), pp. 33–38.

    Google Scholar 

  26. Maher, M.L.; Garza, A.G.S.; “Case-based reasoning in design”; IEEE Expert 12(3) pp. 34–41.

    Google Scholar 

  27. Markus, A.; Renner, G.; Vancza, J.; “Genetic algorithms in free form curve design”; In: Daehlen, M. et al. (eds.); Mathematical Methods for Curves and Surfaces; Vanderbilt University Press, La Vergne, pp. 343–354.

    Google Scholar 

  28. McGuinness, D.L.; Wright, J.R.; “An industrial-strength description logic-based configurator platform”; IEEE Intelligent Systems 13(4) pp. 69–77.

    Google Scholar 

  29. Michalewicz, Z.; Genetic Algorithms + Data Structures = Evolution Programs Springer Verlag, Berlin.

    Google Scholar 

  30. Russel, S.; “Rationality and intelligence”; Artificial Intelligence 94(1–2) pp. 57–77.

    Google Scholar 

  31. Salomons, O.W.; van Slooten, F.; De Koning, G.W.F.; van Houten, F.J.A.M; Kals, H.J.J; “Conceptual graphs in CAD”; Annals of the CIRP 43(1) pp. 125–128.

    Google Scholar 

  32. Sloman, A.; “Explorations in design space”; In Cohn, A.G. (ed.); Proc. of the ECAI-94 Conf; Wiley, New York, pp. 578–582.

    Google Scholar 

  33. Smithers, T.; “Al-based design versus geometry-based design or Why design cannot be supported by geometry alone”; Computer-Aided Design 21(3) pp. 141–150.

    Google Scholar 

  34. Sohlenius, G.; “Concurrent engineering”; Annals of the CIRP 41(2) pp. 645–655.

    Google Scholar 

  35. Steinberg, L; Hall, J.S.; Davison, B.D.; “Highest utility first search across multiple levels of stochastic designs”; In Proc. of the AAAI-98 Conf.; AAAI Press, pp. 477–484.

    Google Scholar 

  36. Sycara, K.P.; “Multiagent systems”; AI Magazine 19(2) pp. 79–92. [Ueda et al., 1997] Ueda, K.; Vaario, J.; Ohkura, K.; “Modeling biological manufacturing systems for dynamic reconfiguration”; Annals of the CIRP 46(1) pp. 343–346.

    Google Scholar 

  37. Umeda, Y.; Tomiyama, T.; “Functional reasoning in design”; IEEE Expert 12(2) pp. 42–28.

    Google Scholar 

  38. Vancza, J.; Markus, A.; “Experiments with the integration of reasoning, optimization and generalization in process planning”; Advances in Engineering Software 25(1) pp. 29–39.

    Google Scholar 

  39. Wegner, P.; “Why interaction is more powerful than algorithms”; Communications of the ACM 40(5) pp. 80–91.

    Google Scholar 

  40. Wolpert, D.H.; Macready, W.G.; “No-free lunch theorems for optimization”; IEEE Trans. on Evolutionary Computation 1(1), pp. 67–82.

    Google Scholar 

  41. Yoshikawa, H.; “Systematization of design knowledge”; Annals of the CIRP 42(1) pp. 131–134.

    Google Scholar 

  42. Yoshikawa, H.; Tomiyama, T.; Kiriyama, T.; Umeda, Y.; “An integrated modelling environment using the metamodel”; Annals of the CIRP 43(1) pp. 121–124.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Váncza, J. (1999). Artificial intelligence support in design: A survey. In: Kals, H., van Houten, F. (eds) Integration of Process Knowledge into Design Support Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1901-8_3

Download citation

  • DOI: https://doi.org/10.1007/978-94-017-1901-8_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5199-8

  • Online ISBN: 978-94-017-1901-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics