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Cognitive Behavior Modeling of Manual Rendezvous and Docking Based on the ACT-R Cognitive Architecture

机译:基于ACT-R认知架构的人工交会对接的认知行为建模

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Astronauts are exposed to numerous stressors during spaceflights, to reduce the faulty operations and improve human performance in manually controlled rendezvous and docking (manual RVD) of space vehicles, a method, which applies sophisticated cognitive architecture Adaptive control of thought-rational (ACT-R ) to model astronaut's cognitive behaviors and investigate the cognitive components influencing human performance, is proposed in this paper . To model the cognitive behaviors in completing manual RVD task, the declarative knowledge of the cognitive processes was obtained from experiments, the procedural knowledge was acquired by analyzing the relationship between cognitive processes and behaviors, and the model parameters were set up according to the boundary conditions and task characteristics. Manual RVD cognitive behavior model is then built up based on the declarative knowledge, the procedural knowledge and the model parameters. Comparisons of model running results and manual control results were performed to test the model's validation. ACT-R control panel tool was also used to analyze the process of model's running and manual control behaviors. Results of the comparisons indicate that the ACT-R model proposed in this paper is in accordance with human cognitive behaviors.
机译:宇航员在太空飞行过程中会暴露于众多压力源下,以减少错误操作并提高航天器手动交会和对接(手动RVD)时的性能,该方法应用了复杂的认知体系结构,对思想理性的自适应控制(ACT-R)本文提出了一种对宇航员的认知行为进行建模并研究影响人类绩效的认知因素的建议。为了完成手动RVD任务中的认知行为建模,通过实验获得了认知过程的声明性知识,通过分析认知过程与行为之间的关系获得了过程知识,并根据边界条件设置了模型参数和任务特征。然后基于声明性知识,过程知识和模型参数建立手动RVD认知行为模型。对模型运行结果和手动控制结果进行了比较,以测试模型的有效性。 ACT-R控制面板工具也用于分析模型运行和手动控制行为的过程。比较结果表明,本文提出的ACT-R模型符合人类的认知行为。

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