Thumbnail
Access Restriction
Subscribed

Author Epstein, S.L. ♦ Wallace, R.J.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2006
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Educational institutions ♦ Natural languages ♦ Humans ♦ Impedance ♦ Clustering algorithms ♦ Artificial intelligence ♦ Frequency ♦ Design for experiments
Abstract Traditional global search heuristics to solve constraint satisfaction problems focus on properties of an individual variable that mandate early search attention. If however, one could predict crucial subproblems (the portions of a constraint satisfaction problem likely to cause each other particular difficulty) in advance, search could address them first. This paper postulates several types of crucial subproblems, and shows how local search can be harnessed to identify them before global search for a solution. A variety of heuristics and metrics are then used to guide traditional constraint heuristics with those crucial subproblems. On certain classes of structured problems, such search outperforms traditional heuristics by at least an order of magnitude in both time and space
Description Author affiliation: Hunter Coll., City Univ. of New York, NY (Epstein, S.L.)
ISBN 0769527280
ISSN 10823409
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2006-11-13
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 234.21 kB
Page Count 12
Starting Page 151
Ending Page 162


Source: IEEE Xplore Digital Library