Solving the 24 puzzle with instance dependent pattern databases

Ariel Felner, Amir Adler

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

29 Scopus citations


A pattern database (PDB) is a heuristic function in a form of a lookup table which stores the cost of optimal solutions for instances of subproblems. These subproblems are generated by abstracting the entire search space into a smaller space called the pattern space. Traditionally, the entire pattern space is generated and each distinct pattern has an entry in the pattern database. Recently, [10] described a method for reducing pattern database memory requirements by storing only pattern database values for a specific instant of start and goal state thus enabling larger PDBs to be used and achieving speedup in the search. We enhance their method by dynamically growing the pattern database until memory is full, thereby allowing using any size of memory. We also show that memory could be saved by storing hierarchy of PDBs. Experimental results on the large 24 sliding tile puzzle show improvements of up to a factor of 40 over previous benchmark results [8].

Original languageEnglish
Title of host publicationAbstraction, Reformulation and Approximation - 6th International Symposium, SARA 2005, Proceedings
PublisherSpringer Verlag
Number of pages13
ISBN (Print)3540278729, 9783540278726
StatePublished - 2005
Externally publishedYes
Event6th International Symposium on Abstraction, Reformulation and Approximation, SARA 2005 - Airth Castle, Scotland, United Kingdom
Duration: 26 Jul 200529 Jul 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3607 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Symposium on Abstraction, Reformulation and Approximation, SARA 2005
Country/TerritoryUnited Kingdom
CityAirth Castle, Scotland


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