Artificial Intelligence and Simulation for Enhanced Pilot Training

This paper discusses the integration of Virtual Constructive (VC) simulation and Convolutional Neural Networks (CNNs) into an Agent-Based Model (ABM) to study pilot performance. By leveraging the strengths of VC for immersive training scenarios and CNN for advanced image recognition and decisionmaking processes, the research aims to provide a comprehensive understanding of how AI and machine learning can help pilot training programs. The paper's series of experiments within the ABM demonstrate the potential of this integrated approach to improve decision accuracy and response times under simulated operational conditions. The findings underscore the effectiveness of integrating VC and CNN into an ABM for training simulations, with implications for pilot training and developing environments that capture operator behavior.