Constraint learning

In constraint satisfaction backtracking algorithms, constraint learning is a techinque for imporoving efficiency. It works by recording new constraints whenever an inconsistency is found. This new constraint may reduce the search space, as future partial evaluations may be found inconsistent without further search.

See also

• Look-ahead (backtracking)
• Backjumping

Reference

• http://www.ics.uci.edu/~dechter/books/index.html. {{cite book}}: Missing or empty |title= (help); Unknown parameter |First= ignored (|first= suggested) (help); Unknown parameter |Last= ignored (|last= suggested) (help); Unknown parameter |Publisher= ignored (|publisher= suggested) (help); Unknown parameter |Title= ignored (|title= suggested) (help); Unknown parameter |Year= ignored (|year= suggested) (help) ISBN 1-55860-890-7