Combining perimeter search and pattern database abstractions

Ariel Feiner, Nir Ofek

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations


A pattern database abstraction (PDB) is a heuristic function in a form of a lookup table. A PDB stores the cost of optimal solutions for instances of abstract problems (subproblems). These costs are used as admissible heuristics for the original problem. Perimeter search (PS) is a form of bidirectional search. First, a breadth-first search is performed backwards from the goal state. Then, a forward search is executed towards the nodes of the perimeter. In this paper we study the effect of combining these two techniques. We describe two methods for doing this. The simplified method uses a regular PDB (towards a single goal state) but uses the perimeter to correct heuristics of nodes outside the perimeter. The second, more advanced method is to build a PDB that stores the cost of reaching any node of the perimeter from a given pattern. Although one might see great potential for speedup in the advanced method, we theoretically show that surprisingly most of the benefit of combining perimeter and PDBs is already exploited by the first method. We also provide experimental results that confirm our findings. We then study the behavior of our new approach when combined with methods for using multiple PDBs such as maxing and adding.

Original languageEnglish
Title of host publicationAbstraction, Reformulation, and Approximation - 7th International Symposium, SARA 2007 Proceedings
PublisherSpringer Verlag
Number of pages14
ISBN (Print)3540735798, 9783540735793
StatePublished - 1 Jan 2007
Event7th International Symposium on Abstraction, Reformulation, and Approximation , SARA 2007 - Whistler, Canada
Duration: 18 Jul 200721 Jul 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4612 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Symposium on Abstraction, Reformulation, and Approximation , SARA 2007

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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