Iterative-deepening Bidirectional Heuristic Search with Restricted Memory

Shahaf S. Shperberg, Steven Danishevski, Ariel Felner, Nathan R. Sturtevant

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

6 Scopus citations

Abstract

The field of bidirectional heuristic search has recently seen great advances. However, the subject of memory-restricted bidirectional search has not received recent attention. In this paper we introduce a general iterative deepening bidirectional heuristic search algorithm (IDBiHS) that searches simultaneously in both directions while controlling the meeting point of the search frontiers. First, we present the basic variant of IDBiHS, whose memory is linear in the search depth. We then add improvements that exploit consistency and front-to-front heuristics. Next, we move to the case where a fixed amount of memory is available to store nodes during the search and develop two variants of IDBiHS: (1) A+IDBiHS, that starts with Aand moves to IDBiHS as soon as memory is exhausted. (2) A variant that stores partial forward frontiers until memory is exhausted and then tries to match each of them from the backward side. Finally, we experimentally compare the new algorithms to existing unidirectional and bidirectional ones. In many cases our new algorithms outperform previous ones in both node expansions and time.

Original languageEnglish
Title of host publication31st International Conference on Automated Planning and Scheduling, ICAPS 2021
EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
PublisherAssociation for the Advancement of Artificial Intelligence
Pages331-339
Number of pages9
ISBN (Electronic)9781713832317
DOIs
StatePublished - 2021
Externally publishedYes
Event31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China
Duration: 2 Aug 202113 Aug 2021

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
Volume2021-August
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Country/TerritoryChina
CityGuangzhou, Virtual
Period2/08/2113/08/21

Bibliographical note

Publisher Copyright:
Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

This work was supported by Israel Science Foundation (ISF) grant #844/17 to Ariel Felner and Eyal Shimony, by BSF grant #2017692, by NSF grant #1815660 and by the Frankel center for CS at BGU. This work was funded by the Canada CIFAR AI Chairs Program; we also acknowledge the support of NSERC.

FundersFunder number
CIFAR AI Chairs
National Science Foundation1815660
Natural Sciences and Engineering Research Council of Canada
United States-Israel Binational Science Foundation2017692
Israel Science Foundation844/17

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