An Integrated Cognitive Architecture for Cognitive Engineering Applications

Abstract

The increasing complexity of computational cognitive architectures may increase both their modeling capabilities and their difficulty to learn and use as cognitive engineering tools. This paper reports our work dedicated to enhance the usability and the cognitive engineering applicability of a complex computational cognitive architecture called QN-ACTR, which integrates two complementary architectures Queueing Network and Adaptive Control of Thought-Rational. The aim is to provide an easy-to-use interface and intuitive modeling that support both inexperienced and experienced users in using this complex and powerful architecture. The process of model development is greatly simplified with improved visualization and validation methods. The results were examined using heuristic evaluation. The benefits and practice implications are discussed.

Queueing network-adaptive control of thought rational (QN-ACTR): an integrated cognitive architecture for modelling complex cognitive and multi-task performance

“…The parameter setup adjusts parameters that control the model performance. QN-ACTR provides two methods to build a model -a text-based syntax method and a click-and-select interface (Cao and Liu, 2012a). The syntax method supports fast and direct model editing (i.e., copy and paste), which is designed for advanced users.…”

“…Using the same experiment platform saves programming labour and, more importantly, avoids any discrepancy between human and model tests caused by different experiment setups. Source: from Cao and Liu (2012a) 3 Model verification…”