Cited by 10Facility Location and Emergency ManagementDisaster Management and ResilienceDisaster Response and Management

Dynamic Resource Allocation During Natural Disasters Using Multi-agent Environment

Vereshchaka, Alina, Dong, Wen·2019·Lecture Notes in Computer Science

Integrity signals

Registry

Crossref · 10.1007/978-3-030-21741-9_13

Cites

2 of 2 references verified0 citation errors · 0 not checkable

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  • The concept of network slice from 5G virtualized networks can be used to create specialized, compartmentalized virtual environments for specific tenants in Digital Twin systems.

    “The concept of slice as elaborated for 5G virtualized networks [164] [165] can be used to create specialized environments that are compartmentalized and devoted to specific tenants, i.e., softwarized virtual environments that reflect the operation of large composed physical environments.”

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Authors
Vereshchaka, A., & Dong, W.
Affiliations
University at Buffalo, State University of New York (US)
Corresponding author
Vereshchaka, Alina
Venue
Lecture Notes in Computer Science
Published
2019
Pages
123-132
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2949317093
Cited by
10
References
2
Citations by year
2025: 3 · 2024: 1 · 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 1
FWCI
5.77
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Facility Location and Emergency Management
  • Social Sciences › Sociology and Political Science › Disaster Management and Resilience
  • Health Sciences › Health Professions › Emergency Medical Services › Disaster Response and Management
Keywords
natural disaster response, multi-agent reinforcement learning, hierarchical reinforcement learning, emergency logistics, real-time decision making

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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