Title of article :
Backjump-based backtracking for constraint satisfaction problems Original Research Article
Author/Authors :
Rina Dechter، نويسنده , , Daniel Frost، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2002
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
Journal title :
Artificial Intelligence
Journal title :
Artificial Intelligence