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Backjump-based backtracking for constraint satisfaction problems
Authors:Rina Dechter  Daniel Frost
Affiliation:Department of Information and Computer Science, University of California, 92697 Irvine, CA, USA
Abstract:The performance of backtracking algorithms for solving finite-domain constraint satisfaction problems can be improved substantially by look-back and look-ahead methods. Look-back techniques extract information by analyzing failing search paths that are terminated by dead-ends. Look-ahead techniques use constraint propagation algorithms to avoid such dead-ends altogether. This paper describes a number of look-back variants including backjumping and constraint recording which recognize and avoid some unnecessary explorations of the search space. The last portion of the paper gives an overview of look-ahead methods such as forward checking and dynamic variable ordering, and discusses their combination with backjumping.
Keywords:Constraint satisfaction   Backtracking   Backjumping   Learning
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