Multi-Agent Modeling and Discrete-Event Simulation for Analyzing the Responsiveness of Pre-Hospital Emergency Services in the Event of Mass Casualties Due to Rare Events - Edjinedja, K.; Elfahim, O.; Arnaud, E.; Barakat, O.; Desmettre, T.; Robert-Nicoud, S.
Mass casualty incidents due to unpredictable events such as natural disasters or epidemics constitute major public health. During these events, Emergency Medical Services (EMS) play a crucial role in the survival of victims. The main purpose of this special issue is to perform 'what if' analyses on the EMS, to test its response in case of mass casualty incidents. The proposed approach provides a methodology for designing a mesoscopic simulation model that integrates Discrete Event Simulation and Agent-Based Simulation. In addition, to evaluate the proposed model, many scenarios have been experimented with to understand and analyze the behavior of EMS. Alternatively, Reinforcement Learning (RL) was used during the simulation stage to learn the optimal resource management strategy. © 2024 IEEE.
Keywords: conferencePaper; Agent-Based Simulation; Discrete Event Sim-ulation; Reinforcement Learning