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AAAI 1998

Generalizing Partial Order and Dynamic Backtracking

Conference Paper Constraint Satisfaction Problems Artificial Intelligence

Abstract

RecentlyFtwo new backtracking algorithmsF dynamic backtracking (DB)and partial order dynamicbacktracking (PDB) have been presented. These algorithms have the property to be additive on disjoint subproblemsand yet use only polynomial space. Unlike DBFPDB only imposes a partial search order and therefore appears to have morefreedomthan DBto explore the search space. HoweverFbothalgorithms are not directly comparable in terms of flexibility. In this paper we present new backtracking algorithms that are obtained by relaxing the ordering conditions of PDB. This gives them additional flexibility while still being additive on disjoint subproblems. In particularF we show that our algorithms generalize both DBand PDB.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
146943727034262785