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Title: The constrainedness of search

Conference ·
OSTI ID:430663
; ;  [1]
  1. Univ. of Strathclyde, Glasgow (United Kingdom)

We introduce a parameter that measures the {open_quotes}constrainedness{close_quotes} of an ensemble of combinatorial problems. If problems are over-constrained, they are likely to be insoluble. If problems are under-constrained, they are likely to be soluble. This constrainedness parameter generalizes a number of parameters previously used in different NP-complete problem classes. Phase transitions in different NP classes can thus be directly compared. This parameter can also be used in a heuristic to guide search. The heuristic captures the intuition of making the most constrained choice first, since it is often useful to branch into the least constrained subproblem. Many widely disparate heuristics can be seen as minimizing constrainedness.

OSTI ID:
430663
Report Number(s):
CONF-960876-; TRN: 96:006521-0038
Resource Relation:
Conference: 13. National conference on artifical intelligence and the 8. Innovative applications of artificial intelligence conference, Portland, OR (United States), 4-8 Aug 1996; Other Information: PBD: 1996; Related Information: Is Part Of Proceedings of the thirteenth national conference on artificial intelligence and the eighth innovative applications of artificial intelligence conference. Volume 1 and 2; PB: 1626 p.
Country of Publication:
United States
Language:
English