Dynamic backtracking

Authors:
Matthew L. Ginsberg
Affiliations:
CIRL, University of Oregon, Eugene, OR
Venue:
Journal of Artificial Intelligence Research
Year:
1993

Citing 3
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Abstract

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.