Dynamic Backtracking

被引:176
作者
Ginsberg, Matthew L. [1 ]
机构
[1] Univ Oregon, CIRL, Eugene, OR 97403 USA
关键词
D O I
10.1613/jair.1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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
引用
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页码:25 / 46
页数:22
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