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Extending the constraint propagation of intervals

Published online by Cambridge University Press:  27 February 2009

Allen C. Ward ,
Tomás Lozano-Pérez  and
Warren P. Seering
Allen C. Ward
Affiliation:
Mechanical Engineering and Applied Mechanics, University of Michigan, Ann Arbor, MI 48109, U.S.A.
Tomás Lozano-Pérez
Affiliation:
Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, U.S.A.
Warren P. Seering
Affiliation:
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, U.S.A.
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Abstract

We show that the usual notion of constraint propagation is but one of a number of similar inferences useful in quantitative reasoning about physical objects. These inferences are expressed formally as rules for the propagation of ‘labeled intervals’ through equations. We prove the rules' correctness and illustrate their utility for reasoning about objects (such as motors or transmissions) which assume a continuum of different states. The inferences are the basis of a ‘mechanical design compiler’, which has correctly produced detailed designs from ‘high level’ descriptions for a variety of power transmission and temperature sensing systems.

Type
Research Article
Information
AI EDAM , Volume 4 , Issue 1 , February 1990 , pp. 47 - 54
Copyright
Copyright © Cambridge University Press 1990

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References

Davis, E. 1987. Constraint propagation with interval labels. Artificial Intelligence, 32, 281–331.Google Scholar
Dixon, J. R., Libardi, E. C. Jr., Luby, S. C., Vaghu, M. and Simmons, M. K. 1985. Expert systems for mechanical design: Examples of symbolic representations of design geometries. In Applications of Knowledge-based Systems to Engineering Analysis and Design, pp. 29–46. New York: ASME.Google Scholar
Fleming, A. 1985. Analysis of uncertainties in a structure of parts. International Joint Conference on Artificial Intelligence.Google Scholar
Gross, M. D. 1985. Design as Exploring Constraints, PhD Thesis, Massachusetts Institute of Technology.Google Scholar
Hamscher, W. 1983. Using Structural and Functional Information in Diagnostic Design. Technical Report 707, MIT Artificial Intelligence Laboratory, June.Google Scholar
Mittal, S., Dym, C. L. and Morjaria, M. 1985. PRIDE: An expert system for the design of paper paths. In Applications of Knowledge-based Systems to Engineering Analysis and Design, pp. 99–116. New York: ASME.Google Scholar
Mostow, J., Steinberg, L., Langrana, N. and Tong, C. 1988. A Domain-independent Model of Knowledge-based Design. Progress Report to the National Science Foundation. Technical Report Working Paper 90–1, Rutgers University.Google Scholar
Popplestone, R. J. 1987. The Edinburgh Designer system as a framework for robotics: the design of behavior. (AI EDAM), 1, 25–36.Google Scholar
Serrano, D. 1989. Constraint Management in Conceptual Design, PhD Thesis, Massachusetts Institute of Technology.Google Scholar
Sussman, G. J. and Steele, G. L. 1980. Constraints—a language for expressing almost hierarchical descriptions. Artificial Intelligence, 14, 1–39.CrossRefGoogle Scholar
Ward, A. C. 1989. A theory of quantitative inference for artifact sets, applied to a mechanical design compiler, PhD Thesis, Massachusetts Institute of Technology.Google Scholar
Ward, A. C. and Seering, W. 1987. An approach to computational aids for mechanical design. In Proceedings 1987 International Conference on Engineering Design. New York: ASME.Google Scholar
Ward, A. C. and Seering, W. 1989 a. The performance of a mechanical design compiler. In Proceedings of the 1989 International Conference on Engineering Design.Google Scholar
Ward, A. C. and Seering, W. 1989 b. Quantitative inference in a mechanical design compiler. In Proceedings of the 1989 ASME Design Theory and Methodology Conference.CrossRefGoogle Scholar