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首页> 外文期刊>International Journal of Industrial Ergonomics >Computational modeling of human performance in multiple monitor environments with ACT-R cognitive architecture
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Computational modeling of human performance in multiple monitor environments with ACT-R cognitive architecture

机译:使用ACT-R认知架构的多监视器环境中的人类绩效的计算建模

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摘要

Much research on modeling human performance associated with visual perception is formulated by schematic models based on neural mechanisms or cognitive architectures. But, these two modeling paradigms are limited in the domains of multiple monitor environments. Although the schematic model based on neural mechanisms can represent human visual systems in multiple monitor environments by providing a detailed account of eye and head movements, these models cannot easily be applied in complex cognitive interactions. On the other hand, the cognitive architectures can model the interaction of multiple aspects of cognition, but these architectures have not focused on modeling the visual orienting behavior of eye and head movements. Thus, in this study, a specific cognitive architecture, which is ACT-R, is extended by an existing schematic model of human visual systems based on neural mechanisms in order to model human performance in multiple monitor environments more accurately. And, this study proposes a method of modeling human performance using the extended ACT-R. The proposed method is validated by an experiment, confirming that the proposed method is able to predict human performance more accurately in multiple monitor environments.
机译:通过基于神经机制或认知体系的示意图模型,开展了许多与视觉感知有关的人类行为建模的研究。但是,这两个建模范例在多个监视器环境的域中受到限制。尽管基于神经机制的示意图模型可以通过提供眼睛和头部运动的详细说明来表示多个监视器环境中的人类视觉系统,但这些模型仍无法轻松地应用于复杂的认知交互中。另一方面,认知体系结构可以对认知的多个方面的交互进行建模,但是这些体系结构并未集中于对眼睛和头部运动的视觉定向行为进行建模。因此,在这项研究中,一种特定的认知体系即ACT-R被基于神经机制的人类视觉系统的现有示意图模型扩展,以便更准确地在多个监视器环境中对人类行为进行建模。并且,本研究提出了一种使用扩展的ACT-R对人类绩效进行建模的方法。通过实验验证了该方法的有效性,证实了该方法能够在多个监视器环境中更准确地预测人类的表现。

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