Comparing front-to-front and front-to-end heuristics in bidirectional search

Lior Siag, Shahaf S. Shperberg, Ariel Felner, Nathan R. Sturtevant

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Most recent theoretical and algorithmic work in bidirectional heuristic search (BiHS) used front-to-end (F2E) heuristics that estimate the distance to the start and goal states. In this paper, we start exploring front-to-front (F2F) heuristics, which estimate the distance between any pair of states. Devising efficient algorithms that use F2F heuristics is a challenging task. Thus, it is important to first understand the benefits of using F2F heuristics compared to F2E heuristics. To this end, we theoretically and experimentally demonstrate that there is a great potential in using F2F heuristics implying that F2F BiHS is a promising area of future research.

Original languageEnglish
Pages (from-to)158-162
Number of pages5
JournalThe International Symposium on Combinatorial Search
Volume16
Issue number1
DOIs
StatePublished - 2023
Externally publishedYes
Event16th International Symposium on Combinatorial Search, SoCS 2023 - Prague, Czech Republic
Duration: 14 Jul 202316 Jul 2023

Bibliographical note

Publisher Copyright:
© 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org).

Funding

This research was supported by The Israel US Binational Science Foundation (BSF) grant 2021643 to Ariel Felner. This work was partially funded by the Canada CIFAR AI Chairs Program. We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC).

FundersFunder number
United States - Israel Binational Science Foundation
Natural Sciences and Engineering Research Council of Canada
United States-Israel Binational Science Foundation2021643

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