QN-ACTR Modeling of Multitask Performance of Dynamic and Complex Cognitive Tasks

Abstract

This paper reports the latest development of QN-ACTR, which integrates two complementary cognitive architectures, Queueing Network and Adaptive Control of Thought-Rational. The integrated architecture can model multitask performance in dynamic and complex cognitive task situations that each architecture alone has difficulties to model. It also allows the examination of several important modeling issues in ACTR from the QN perspective. Benefits from the integration are illustrated in model simulation of a transcription typing and reading comprehension dual-task. Future steps of the integration are discussed.