Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds

Lior Siag; Shahaf Shperberg; Ariel Felner; Nathan Sturtevant

Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds

Lior Siag, Shahaf Shperberg, Ariel Felner, Nathan Sturtevant

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Recent research on bidirectional heuristic search (BiHS) is based on the must-expand pairs theory (MEP theory), which describes which pairs of nodes must be expanded during the search to guarantee the optimality of solutions. A separate line of research in BiHS has proposed algorithms that use lower bounds that are derived from consistent heuristics during search. This paper links these two directions, providing a comprehensive unifying view and showing that both existing and novel algorithms can be derived from the MEP theory. An extended set of bounds is formulated, encompassing both previously discovered bounds and new ones. Finally, the bounds are empirically evaluated by their contribution to the efficiency of the search.

Original language	English
Title of host publication	Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Editors	Edith Elkind
Publisher	International Joint Conferences on Artificial Intelligence
Pages	5631-5638
Number of pages	8
ISBN (Electronic)	9781956792034
State	Published - 2023
Externally published	Yes
Event	32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 - Macao, China Duration: 19 Aug 2023 → 25 Aug 2023

Publication series

Name	IJCAI International Joint Conference on Artificial Intelligence
Volume	2023-August
ISSN (Print)	1045-0823

Conference

Conference	32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Country/Territory	China
City	Macao
Period	19/08/23 → 25/08/23

Bibliographical note

Publisher Copyright:
© 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.

Funding

This research was supported by the US-Israel Binational Science Foundation (BSF) grant no. 2021643. This work was also funded by the Canada CIFAR AI Chairs Program. We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC).

Funders	Funder number
Natural Sciences and Engineering Research Council of Canada
United States-Israel Binational Science Foundation	2021643

Cite this

Siag, L., Shperberg, S., Felner, A., & Sturtevant, N. (2023). Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds. In E. Elkind (Ed.), Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 (pp. 5631-5638). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August). International Joint Conferences on Artificial Intelligence.

Siag, Lior ; Shperberg, Shahaf ; Felner, Ariel et al. / Front-to-End Bidirectional Heuristic Search with Consistent Heuristics : Enumerating and Evaluating Algorithms and Bounds. Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. editor / Edith Elkind. International Joint Conferences on Artificial Intelligence, 2023. pp. 5631-5638 (IJCAI International Joint Conference on Artificial Intelligence).

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abstract = "Recent research on bidirectional heuristic search (BiHS) is based on the must-expand pairs theory (MEP theory), which describes which pairs of nodes must be expanded during the search to guarantee the optimality of solutions. A separate line of research in BiHS has proposed algorithms that use lower bounds that are derived from consistent heuristics during search. This paper links these two directions, providing a comprehensive unifying view and showing that both existing and novel algorithms can be derived from the MEP theory. An extended set of bounds is formulated, encompassing both previously discovered bounds and new ones. Finally, the bounds are empirically evaluated by their contribution to the efficiency of the search.",

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Siag, L, Shperberg, S, Felner, A & Sturtevant, N 2023, Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds. in E Elkind (ed.), Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. IJCAI International Joint Conference on Artificial Intelligence, vol. 2023-August, International Joint Conferences on Artificial Intelligence, pp. 5631-5638, 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023, Macao, China, 19/08/23.

Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds. / Siag, Lior; Shperberg, Shahaf; Felner, Ariel et al.
Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. ed. / Edith Elkind. International Joint Conferences on Artificial Intelligence, 2023. p. 5631-5638 (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Siag L, Shperberg S, Felner A, Sturtevant N. Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds. In Elkind E, editor, Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. International Joint Conferences on Artificial Intelligence. 2023. p. 5631-5638. (IJCAI International Joint Conference on Artificial Intelligence).

Front-to-End Bidirectional Heuristic Search with Consistent Heuristics: Enumerating and Evaluating Algorithms and Bounds

Abstract

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