Revision as of 12:21, 10 February 2006 edit Tizio (talk \| contribs) Extended confirmed users 13,768 edits modified Graph-based learning, added jumpback learning and meta-techniques ← Previous edit		Revision as of 15:46, 10 February 2006 edit undo Tizio (talk \| contribs) Extended confirmed users 13,768 edits →Jumpback learning: which assignment is used Next edit →
Line 34: ==Jumpback learning== Jumpback learning is based on storing as ~~constraint~~constraints the inconsistent assignments that would be found by [[conflict-based backjumping]]. Whenever a partial assignment is found inconsistent, this algorithm selects the violated constraint that is minimal according to an ordering based on the order of instantiation of varibles. The evaluation restricted of the variables that are in this constraint is inconsistent and is usually shorter than the complete evaluation. Jumpback learning stores this fact as a new constraint. The ordering on constraints is based on the order of assignment of variable. In particular, the least of two constraint is the one whose latest non-common variable has been instantiated first. When an inconsistent assignment is reached, jumpback learning selects the violated constraint that is minimal according to this ordering, and restricts the current assignment to its variables. The constraint expressing the inconsistency of this assignment is stored. ==Meta-techniques==

Constraint learning: Difference between revisions