Abstract
We present MM, the first bidirectional heuristic search algorithm whose forward and backward searches are guaranteed to "meet in the middle", i.e. never expand a node beyond the solution midpoint. We also present a novel framework for comparing MM, A∗, and brute-force search, and identify conditions favoring each algorithm. Finally, we present experimental results that support our theoretical analysis.
Original language | English |
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Title of host publication | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 |
Publisher | AAAI press |
Pages | 3411-3417 |
Number of pages | 7 |
ISBN (Electronic) | 9781577357605 |
State | Published - 2016 |
Externally published | Yes |
Event | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States Duration: 12 Feb 2016 → 17 Feb 2016 |
Publication series
Name | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 |
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Conference
Conference | 30th AAAI Conference on Artificial Intelligence, AAAI 2016 |
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Country/Territory | United States |
City | Phoenix |
Period | 12/02/16 → 17/02/16 |
Bibliographical note
Publisher Copyright:© Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Funding
Thanks to Joseph Barker for answering questions and providing extra data related to (Barker and Korf 2015) and to Sandra Zilles and Andre Grahl Pereira for suggesting improvements in the theoretical analysis of MM. Financial support for this research was in part provided by Canada's Natural Science and Engineering Research Council (NSERC) and by Israel Science Foundation (ISF) grant #417/13. Computational facilities for some of our experiments were provided by Compute Canada. This material is based upon work supported by the National Science Foundation under Grant No. 1551406.
Funders | Funder number |
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National Science Foundation | 1551406 |
Compute Canada | |
Natural Sciences and Engineering Research Council of Canada | |
Israel Science Foundation | 417/13 |