A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates

Eyal Weiss; Ariel Felner; Gal A. Kaminka

A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates

Eyal Weiss
, Ariel Felner
, Gal A. Kaminka

Department of Computer Science and Artificial Intelligence

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › 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. 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 several generalized variants of the shortest path problem. We introduce the problem of finding a path with the tightest lower-bound on the optimal cost. We then present two complete algorithms for the generalized problem, and empirically demonstrate their efficacy.

Original language	English
Title of host publication	Proceedings of the ICAPS-23 Workshop on Reliable Data-Driven Planning and Scheduling (RDDPS)
State	Published - 2023

Bibliographical note

An improved version appears in the European Conference on Artificial Intelligence (ECAI) 2023

1 Conference contribution

A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates
Weiss, E., Felner, A. & Kaminka, G. A., 28 Sep 2023, ECAI 2023 - 26th European Conference on Artificial Intelligence, including 12th Conference on Prestigious Applications of Intelligent Systems, PAIS 2023 - Proceedings. Gal, K., Gal, K., Nowe, A., Nalepa, G. J., Fairstein, R. & Radulescu, R. (eds.). IOS Press BV, p. 2607-2614 8 p. (Frontiers in Artificial Intelligence and Applications; vol. 372).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Open Access
2 Scopus citations

Cite this

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title = "A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates",

abstract = "The shortest path problem in graphs is a cornerstone of AI theory and applications. Existing algorithms generally ignore edge weight computation time. 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 several generalized variants of the shortest path problem. We introduce the problem of finding a path with the tightest lower-bound on the optimal cost. We then present two complete algorithms for the generalized problem, and empirically demonstrate their efficacy.",

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note = "An improved version appears in the European Conference on Artificial Intelligence (ECAI) 2023",

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A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates

Abstract

Bibliographical note

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Research output

A Generalization of the Shortest Path Problem to Graphs with Multiple Edge-Cost Estimates

Cite this