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A disaster multiagent coordination simulation system to evaluate the design of a first-response team

机译:灾难多主体协作模拟系统,用于评估急救团队的设计

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Identifying the best design configuration for a first-response team is important for minimizing total operation time and reducing the human cost of natural and manmade disasters. This paper presents ongoing research that focuses on a disaster multiagent coordination simulation (DMCsim) system that is able to optimally design the first-response team and evaluate the team design configuration before initiation of a search and rescue operation. We developed an agent-based simulation system that uses machine learning techniques and design of experiments methods to test different configuration setups and determine the effects of various factors on operation completion time. The evaluation of a team design for a disaster-response operation revealed that some design factors have a significant effect on operation outcome. Removing the effects of uncontrollable factors, such as damage level and robot reliability, yielded a robust team design that could function in a particular disaster environment regardless of the effects of such factors. The DMCsim assists decision makers to evaluate an emergency-response operation, revise the current strategy based on resources on hand, redesign the available team, and visually track operation performance before launching the actual team in the disaster field. This research extends previous disaster response coordination systems by proposing a new simulation model and evaluating a first-response team design.
机译:为第一响应团队确定最佳设计配置,对于最大程度地减少总运营时间并减少自然和人为灾难的人工成本至关重要。本文介绍了正在进行的研究,其重点是灾难多主体协调模拟(DMCsim)系统,该系统能够在搜寻和营救行动启动之前优化设计第一响应团队并评估团队的设计配置。我们开发了基于代理的仿真系统,该系统使用机器学习技术和实验方法设计来测试不同的配置设置,并确定各种因素对操作完成时间的影响。对灾难响应操作的团队设计的评估表明,一些设计因素对操作结果有重大影响。消除不可控因素(如损坏程度和机器人可靠性)的影响后,团队设计稳健,无论这些因素的影响如何,它都可以在特定的灾难环境中发挥作用。 DMCsim可帮助决策者评估紧急行动,基于手头资源修改当前策略,重新设计可用的团队并在启动灾难现场的实际团队之前直观地跟踪运营绩效。这项研究通过提出新的仿真模型并评估第一响应团队设计,扩展了先前的灾难响应协调系统。

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