DocumentCode
2390170
Title
Selective relaxation for constraint satisfaction problems
Author
Freuder, E.C. ; Wallace, R.J.
Author_Institution
Dept. of Comput. Sci., New Hampshire Univ., Durham, NH, USA
fYear
1991
fDate
10-13 Nov 1991
Firstpage
332
Lastpage
339
Abstract
A basic problem is to optimize the tradeoff between effort required to establish a local consistency and that required for search. An approach is presented to this problem which is termed selective relaxation. The idea is to perform consistency checking at places where it is likely to be effective, basing this judgment on local criteria. To this end, the authors introduce two forms of bounded relaxation, one in which consistency testing propagates for a limited distance from a point of change, and one in which it stops when the amount of change, or response, falls below threshold. Experiments show that these procedures can outperform well-known preprocessing or hybrid algorithms on many problems
Keywords
artificial intelligence; constraint theory; bounded relaxation; consistency checking; constraint satisfaction problems; hybrid algorithms; local consistency; local criteria; selective relaxation; Artificial intelligence; Computer science; Data preprocessing; Performance evaluation; Relaxation methods; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
Conference_Location
San Jose, CA
Print_ISBN
0-8186-2300-4
Type
conf
DOI
10.1109/TAI.1991.167112
Filename
167112
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