Steps Towards Integrated Models of Cognitive Systems: A Levels-of-Analysis Approach to Comparing Human Performance to Model Predictions in a Complex Task Environment

Attempts to model complex task environments can serve as benchmarks that enable us to assess the state of cognitive theory and to identify productive topics for future research. Such models must be accompanied by a thorough examination of their fit to overall performance as well as their detailed fit to the microstructure of performance. We provide an example of this approach in our Argus Prime Model of a complex simulated radar operator task that combines realtime demands on human cognitive, perceptual, and action with a dynamic decision-making task. The generally good fit of the model to overall performance is a mark of the power of contemporary cognitive theory and architectures of cognition. The multiple failures of the model to capture fine-grained details of performance mark the limits of contemporary theory and signal productive areas for future research.