Bridging Cognitive Modeling and Pilot Training: A QN-ACTR Model for Complex Flight Tasks

This paper presents advances in bridging computational cognitive modeling with practical pilot training applications. Using the Queueing Network-Adaptive Control of Thought-Rational (QN-ACTR) cognitive architecture, we developed a comprehensive pilot model capable of performing complex flight tasks. The model integrates perceptual, cognitive, and motor processes to simulate realistic pilot behavior during demanding flight scenarios. This work demonstrates how cognitive architecture-based models can inform competency-based training design and provide objective metrics for pilot performance assessment. The findings contribute to the ongoing transformation of aviation training toward more data-driven and evidence-based approaches.