Title :
Solving n-ary constraint labeling problems using incremental subnetwork consistency
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
Abstract :
Presents an algorithm for finding all solutions of n-ary constraint labeling problems while building constraint networks. The key principle of the algorithm alternating the instantiation of a newly chosen variable, and making the domain values, of already-instantiated variables consistent among them, until all variables are considered. The algorithm chooses variables for domain instantiation one at a time; assigns all viable domain values to it; adds the variable to the constraint network; and achieves consistencies within subnetworks of the nonfuture variables, in an incremental manner. In this algorithm, any inconsistent domain values are eliminated once and for all. The proposed constraint labeling algorithm does not exhibit the stacking-unstacking problem which most hybrid algorithms have. In addition, this algorithm is more efficient than E.C. Freuder´s (1978) constraint synthesis algorithm because the latter attempts to achieve strong k-consistencies over n variables
Keywords :
constraint theory; constraint networks; domain values; incremental subnetwork consistency; n-ary constraint labeling problems; nonfuture variables; variable instantiation; Artificial intelligence; Filtering algorithms; Labeling; Network synthesis; Operations research; Search problems;
Conference_Titel :
Artificial Intelligence Applications, 1991. Proceedings., Seventh IEEE Conference on
Conference_Location :
Miami Beach, FL
Print_ISBN :
0-8186-2135-4
DOI :
10.1109/CAIA.1991.120891