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Journal of Computer and System Sciences
Article . 2026 . Peer-reviewed
License: CC BY
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY
Data sources: Datacite
DBLP
Conference object . 2024
Data sources: DBLP
DBLP
Preprint . 2024
Data sources: DBLP
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Exploration of graphs with excluded minors

Authors: Júlia Baligács; Yann Disser; Irene Heinrich; Pascal Schweitzer;

Exploration of graphs with excluded minors

Abstract

We study the online graph exploration problem proposed by Kalyanasundaram and Pruhs (1994) and prove a constant competitive ratio on minor-free graphs. This result encompasses and significantly extends the graph classes that were previously known to admit a constant competitive ratio. The main ingredient of our proof is that we find a connection between the performance of the particular exploration algorithm Blocking and the existence of light spanners. Conversely, we exploit this connection to construct light spanners of bounded genus graphs. In particular, we achieve a lightness that improves on the best known upper bound for genus g>0 and recovers the known tight bound for the planar case (g=0).

to appear at ESA 2023

Country
Germany
Keywords

FOS: Computer and information sciences, online algorithms, Discrete Mathematics (cs.DM), Computer Science - Data Structures and Algorithms, competitive analysis, Data Structures and Algorithms (cs.DS), bounded genus graphs, graph spanners, minor-free graphs, 004, graph exploration, Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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