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ABMS-Driven Reinforcement Learning for Dynamic Resource Allocation in Mass Casualty Incidents †

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Pubblicato in:Future Internet vol. 17, no. 11 (2025), p. 502-516
Autore principale: Ionuț, Murarețu
Altri autori: Vultureanu-Albiși Alexandra, Ilie Sorin, Costin, Bădică
Pubblicazione:
MDPI AG
Soggetti:
Romania
Emergency medical care
Machine learning
Simulation
Decision support systems
Artificial intelligence
Adaptability
Assignment problem
Hospitals
Optimization techniques
Evacuations & rescues
Decision making
Survival
Optimization
Resource allocation
Emergency response
Linear programming
Mixed integer
Mass casualty incidents
Constraints
Agent-based models
Accesso online:Citation/Abstract
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