A generalization of the shortest path problem to graphs with multiple edge-cost estimates (Student abstract)

Eyal Weiss

doi:10.1609/socs.v16i1.27316

A generalization of the shortest path problem to graphs with multiple edge-cost estimates (Student abstract)

Eyal Weiss

Department of Computer Science

Research output: Contribution to journal › Conference article › peer-review

Abstract

The shortest path problem in graphs is a cornerstone of AI theory and applications. Existing algorithms generally ignore edge weight computation time. In this paper we present a generalized framework for weighted directed graphs, where edge weight can be computed (estimated) multiple times, at increasing accuracy and run-time expense. This raises a generalized shortest path problem that optimizes different aspects of path cost and its uncertainty. We describe in high-level a complete anytime algorithm for the generalized problem and discuss possible future extensions.

Original language	English
Pages (from-to)	206-207
Number of pages	2
Journal	The International Symposium on Combinatorial Search
Volume	16
Issue number	1
DOIs	https://doi.org/10.1609/socs.v16i1.27316
State	Published - 2023
Event	16th International Symposium on Combinatorial Search, SoCS 2023 - Prague, Czech Republic Duration: 14 Jul 2023 → 16 Jul 2023

Bibliographical note

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

Funding

Eyal Weiss is supported by the Adams Fellowship Program of the Israel Academy of Sciences and Humanities and Bar- Ilan University President’s Scholarship. The research was partially funded by ISF Grant #2306/18 and BSF-NSF grant 2017764. Thanks to K. Ushi.

Funders	Funder number
BSF-NSF	2017764
Israel Academy of Sciences and Humanities
Israel Science Foundation	2306/18

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10.1609/socs.v16i1.27316

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A generalization of the shortest path problem to graphs with multiple edge-cost estimates (Student abstract)

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