Proposal of ACT-R cognitive modeling method for Stroop Task based on quantitative prediction of mental workload

Abstract

The Stroop task is used to understand human errors in cognitive processing, particularly in the context of ACT-R cognitive architecture. In existing ACT-R models, the Stroop effect is driven by the competition between intuitive and deliberate processes. However, it is difficult to determine criteria for intuition and deliberation. In this study, we propose a new method based on dual process theory for the Stroop task. We represent the switches between intuitive and deliberate processes through the quantitative prediction value of cognitive load based on ACTR. The proposed cognitive model shows a relatively good representation of the Stroop effect, as demonstrated by the validation experiment. This method contributes to the expansion of the ACT-R modeling field by enabling the representation of human errors due to intuitive decisions in the Stroop task.