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.
