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Developing an agent model of human performance in air traffic control operations using Apex cognitive architecture

机译:使用Apex认知架构开发空中交通管制运营中人员绩效的代理模型

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For the analysis of large-scale complex systems, agent-based modeling and simulation has proven to provide a valuable research tool. The emphasis has, however, typically been on representing the dynamic behavior of physical entities such as aircraft. Simulation of human operators has often been minimal even though human behavior has an enormous impact on overall system performance and safety. Therefore, human capabilities and limitations need to be taken into account early in the system design process before irrevocable choices have been made. This paper reports on the development of agent models with human-like performance characteristics using a cognitive architecture. We present an agent model of an air traffic controller that is developed and incorporated into an agent-based simulation of the national airspace to support the design and evaluation of advanced air transportation concepts.
机译:对于大型复杂系统的分析,基于代理的建模和仿真已被证明可以提供有价值的研究工具。但是,重点通常是表示物理实体(例如飞机)的动态行为。即使人的行为对整个系统的性能和安全性产生巨大的影响,对操作员的仿真通常也很少。因此,在做出不可撤销的选择之前,必须在系统设计过程的早期就考虑人员的能力和局限性。本文报告了使用认知架构开发具有类似人的性能特征的代理模型的过程。我们提出了一种空中交通管制员的代理模型,该模型已开发并纳入国家空域的基于代理的模拟中,以支持高级航空运输概念的设计和评估。

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