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Dynamic variable elimination during propagation solving
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International Conference on Principles and Practice of Declarative Programming archive
Proceedings of the 10th international ACM SIGPLAN conference on Principles and practice of declarative programming table of contents
Valencia, Spain
SESSION: Constraints table of contents
Pages 247-257  
Year of Publication: 2008
ISBN:978-1-60558-117-0
Authors
Christian Schulte  ICT, KTH - Royal Institute of Technology, Stockholm, Sweden
Peter J. Stuckey  University of Melbourne, Australia
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Constraint propagation solvers interleave propagation (removing impossible values from variables domains) with search. Propagation is performed by executing propagators (removing values) implementing constraints (defining impossible values). In order to specify constraint problems with a propagation solver often many new intermediate variables need to be introduced. Each variable plays a role in calculating the value of some expression. But as search proceeds not all of these expressions will be of interest any longer, but the propagators implementing them will remain active. In this paper we show how we can analyse the propagation graph of the solver in linear time to determine intermediate variables that can be removed without effecting the result. Experiments show that applying this analysis can reduce the space and time requirements for constraint propagation on example problems


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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Collaborative Colleagues:
Christian Schulte: colleagues
Peter J. Stuckey: colleagues