Maximizing over multiple pattern databases speeds up heuristic search

Robert C. Holte; Ariel Felner; Jack Newton; Ram Meshulam; David Furcy

doi:10.1016/j.artint.2006.09.002

Maximizing over multiple pattern databases speeds up heuristic search

Robert C. Holte, Ariel Felner, Jack Newton, Ram Meshulam, David Furcy

Software Engineering Program

Research output: Contribution to journal › Article › peer-review

56 Scopus citations

Abstract

A pattern database (PDB) is a heuristic function stored as a lookup table. This paper considers how best to use a fixed amount (m units) of memory for storing pattern databases. In particular, we examine whether using n pattern databases of size m / n instead of one pattern database of size m improves search performance. In all the state spaces considered, the use of multiple smaller pattern databases reduces the number of nodes generated by IDA*. The paper provides an explanation for this phenomenon based on the distribution of heuristic values that occur during search.

Original language	English
Pages (from-to)	1123-1136
Number of pages	14
Journal	Artificial Intelligence
Volume	170
Issue number	16-17
DOIs	https://doi.org/10.1016/j.artint.2006.09.002
State	Published - 1 Nov 2006

Keywords

Admissible heuristics
Heuristic search
IDA*
Pattern databases

ASJC Scopus subject areas

Language and Linguistics
Linguistics and Language
Artificial Intelligence

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10.1016/j.artint.2006.09.002

Cite this

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title = "Maximizing over multiple pattern databases speeds up heuristic search",

abstract = "A pattern database (PDB) is a heuristic function stored as a lookup table. This paper considers how best to use a fixed amount (m units) of memory for storing pattern databases. In particular, we examine whether using n pattern databases of size m / n instead of one pattern database of size m improves search performance. In all the state spaces considered, the use of multiple smaller pattern databases reduces the number of nodes generated by IDA*. The paper provides an explanation for this phenomenon based on the distribution of heuristic values that occur during search.",

keywords = "Admissible heuristics, Heuristic search, IDA*, Pattern databases",

author = "Holte, {Robert C.} and Ariel Felner and Jack Newton and Ram Meshulam and David Furcy",

note = "Funding Information: This research was supported in part by the Israeli Science Foundation under grant No 728/06, and by a Discovery grant and a postgraduate scholarship from the Natural Sciences and Engineering Research Council of Canada and an Alberta iCore postgraduate fellowship. This research was also partly supported by NSF awards to Sven Koenig under contracts IIS-9984827 and IIS-0098807. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the sponsoring organizations, agencies, companies or the US government.",

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AU - Furcy, David

N1 - Funding Information: This research was supported in part by the Israeli Science Foundation under grant No 728/06, and by a Discovery grant and a postgraduate scholarship from the Natural Sciences and Engineering Research Council of Canada and an Alberta iCore postgraduate fellowship. This research was also partly supported by NSF awards to Sven Koenig under contracts IIS-9984827 and IIS-0098807. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the sponsoring organizations, agencies, companies or the US government.

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Maximizing over multiple pattern databases speeds up heuristic search

Abstract

Keywords

ASJC Scopus subject areas

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