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
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;
Conference_Titel :
Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-8186-2300-4
DOI :
10.1109/TAI.1991.167112