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An Integrated Working Memory Model for Time-Based Resource-Sharing

机译:用于基于时间的资源共享的集成工作内存模型

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The time-based resource-sharing (TBRS) model envisions working memory as a rapidly switching, serial, attentional refreshing mechanism. Executive attention trades its time between rebuilding decaying memory traces and processing extraneous activity. To thoroughly investigate the implications of the TBRS theory, we integrated TBRS within the ACT-R cognitive architecture, which allowed us to test the TBRS model against both participant accuracy and response time data in a dual task environment. In the current work, we extend the model to include articulatory rehearsal, which has been argued in the literature to be a separate mechanism from attentional refreshing. Additionally, we use the model to predict performance under a larger range of cognitive load (CL) than typically administered to human subjects. Our simulations support the hypothesis that working memory capacity is a linear function of CL and suggest that this effect is less pronounced when articulatory rehearsal is available.An Integrated Working Memory Model for Time-Based Resource-Sharing proposes a formalized a theory of working memory, time-based resource sharing (TBRS), within the ACT-R cognitive architecture. Instantiating the theory within ACT-R allowed the authors to predict task accuracy and response times when an articulatory rehearsal mechanism was included with the TBRS mechanism. This paper was awarded the Allen Newell Award for the best student- led paper submitted to ICCM 2018 for their research efforts.
机译:基于时间的资源共享(TBRS)模型将工作内存设想为一种快速切换,串行,注意刷新的机制。行政人员的注意力在重建衰退的记忆痕迹和处理无关的活动之间进行权衡。为了彻底研究TBRS理论的含义,我们将TBRS集成到ACT-R认知体系结构中,这使我们能够在双重任务环境中针对参与者的准确性和响应时间数据测试TBRS模型。在当前的工作中,我们将模型扩展为包括发音排练,这在文献中被认为是与注意力刷新无关的机制。此外,我们使用该模型预测认知负荷(CL)的范围要比通常应用于人类受试者的表现大。我们的模拟支持以下假设:工作记忆容量是CL的线性函数,并表明当进行演练时,这种影响不太明显。基于时间的资源共享的集成工作记忆模型提出了一种形式化的工作记忆理论, ACT-R认知架构内的基于时间的资源共享(TBRS)。在ACT-R中实例化该理论可以使作者预测在TBRS机制中包含发音排练机制时的任务准确性和响应时间。该论文被授予艾伦·纽厄尔奖(Allen Newell Award),以表彰其为研究工作提交给ICCM 2018的最佳学生报告。

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