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Management of conflict for preliminary engineering design tasks

Published online by Cambridge University Press:  27 February 2009

Djamila Haroud
Affiliation:
Artificial Intelligence Laboratory (LIA)
Sylvie Boulanger
Affiliation:
ICOM (Steel Structures), Swiss Federal Institute of Technology (EPFL), IN-Ecublens, 1015 Lausanne, Switzerland
Esther Gelle
Affiliation:
Artificial Intelligence Laboratory (LIA)
Ian Smith
Affiliation:
Artificial Intelligence Laboratory (LIA)

Abstract

Much of preliminary engineering design is a constraint-driven non-monotonic exploration process. Initial decisions are made when information is incomplete and many goals are contradictory. Such conditions are present regardless of whether one or several designers contribute to designs. This paper presents an approach for supporting decisions in situations of incomplete and conflicting knowledge. In particular, we use assumptions and conflict management to achieve efficient search in contexts where little reliable information exists. A knowledge representation, containing a semantic differentiation between two types of assumptions, is used within a computational model based on the dynamic constraint satisfaction paradigm. Conflict management strategies consist of three generic mechanisms adapted to the type of constraints involved. These strategies may be refined through consideration of variable importance, context, and design inertia.

Type
Articles
Copyright
Copyright © Cambridge University Press 1995

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References

REFERENCES

Baykan, C.A., & Fox, M.S. (1992). WRIGHT: A constraint-based spatial layout system. In Artificial Intelligence in Design, (Tong, and Siriam, , Eds.), Vol. 1, pp. 395432. Academic Press, Inc., New York.Google Scholar
Bowen, J., & Bahler, D. (1992a). Supporting multiple perspectives. A constraint-based approach to concurrent engineering. In Artificial Intelligence in Design '92, (Gero, J.S., Ed.), pp. 8597. Kluwer Academic Publishers.Google Scholar
Bowen, J., & Bahler, D. (1992b). Frames, quantification, perspectives and negotiation in constraint network for life-cycle engineering. Int. J. Artif. Intell. Eng. 7(4), 119226.Google Scholar
De Kleer, J. (1986). An assumption-based truth maintenance system. Artif. Intell. 28, 127161.Google Scholar
Doyle, J. (1979). A truth maintenance system. Artif. Intell. 12, 231275.Google Scholar
Faltings, B., Haroud, D., & Smith, I. (1992). Dynamic constraint propagation with continuous variables. In Proc. Tenth Europ. Conf. Artif. Intell., 754758. Bernd Neumann, Vienna.Google Scholar
Haroud, D., & Faltings, B. (1994). Global consistency for continuous variables. In Proc. Eleventh Europ. Conf. Artif. Intell., pp. 115119. Amsterdam.Google Scholar
Krishnan, V., Navinchandra, D., Rane, P., & Rinderle, J.R. (1990). Constraint reasoning and planning in concurrent design. Tech. Rep. CMU-RI-TR-90–03, Carnegie Mellon University.Google Scholar
Logan, B.S., Corne, D.W., & Smithers, T. (1992). Enduring support. In Artificial Intelligence in Design '92, (Gero, J.S., Ed.), pp. 433454. Kluwer Academic Publishers, Dordrecht, The Netherlands.Google Scholar
Mackworth, A. (1977). Consistency in networks of relations. Artif. Intell. 8, 99118.CrossRefGoogle Scholar
Mittal, S., & Falkenheiner, B. (1990). Dynamic constraint satisfaction problems. In Proc. Eighth Nat. Conf. Artif. Intell., pp. 2532. Boston.Google Scholar
Petrie, C.J. (1991). Context maintenance. In Proc. Ninth Nat. Conf. Artif. Intell., pp. 288295. Anaheim.Google Scholar
Sham, S.H.R. (1993). Nonmonotonic reasoning in design. J. Comput. Civil Eng. 7(1), 3653.CrossRefGoogle Scholar