AAAI 1998
Generalizing Partial Order and Dynamic Backtracking
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