ML p(r)ior | Dynamic Backtracking
Processing...

Dynamic Backtracking

1993-08-01
9308101 | cs.AI
Because of their occasional need to return to shallow points in a search tree, existing backtracking methods can sometimes erase meaningful progress toward solving a search problem. In this paper, we present a method by which backtrack points can be moved deeper in the search space, thereby avoiding this difficulty. The technique developed is a variant of dependency-directed backtracking that uses only polynomial space while still providing useful control information and retaining the completeness guarantees provided by earlier approaches.
PDF

Highlights - Most important sentences from the article

Login to like/save this paper, take notes and configure your recommendations