| Hierarchical nonlinear constraint satisfaction |
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Symposium on Applied Computing
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Proceedings of the 2004 ACM symposium on Applied computing
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Nicosia, Cyprus
SESSION: AI and computational logic and image analysis (AI)
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Pages: 16 - 20
Year of Publication: 2004
ISBN:1-58113-812-1
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Author
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Hiroshi Hosobe
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National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
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Downloads (6 Weeks): 6, Downloads (12 Months): 29, Citation Count: 0
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ABSTRACT
Constraint programming is a method of problem solving that allows declarative specification of relations among objects. It is important to allow preferences of constraints since it is often difficult for programmers to specify all constraints without conflicts. In this paper, we propose a numerical method for solving nonlinear constraints with hierarcical preferences (i.e., constraint hierarchies) in a least-squares manner. This method finds sufficiently precise local optimal solutions by appropriately processing hierarchical preferences of constraints. To evaluate the effectiveness of our method, we present experimental results obtained with a prototype constraint solver.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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F. Benhamou and M. Ceberio. Soft constraints: A unifying framework applied to continuous soft constraints. In Proc. Workshop of the ERCIM Working Group on Constraints and the CoLogNET Area on Constraint and Logic Programming, 2003.
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A. Björck. Numerical Methods for Least Squares Problems. SIAM, 1996.
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Alan Borning , Kim Marriott , Peter Stuckey , Yi Xiao, Solving linear arithmetic constraints for user interface applications, Proceedings of the 10th annual ACM symposium on User interface software and technology, p.87-96, October 14-17, 1997, Banff, Alberta, Canada
[doi> 10.1145/263407.263518]
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