TIGARS guidance on confidence in simulation for ML assurance

Overview

Compares virtual simulation, hardware-in-the-loop, controlled trials and real-world trials for ML training and verification. TIGARS experience motivates explicit confidence arguments for simulator software, sensor fidelity and results, proportionate to the purpose and risk of the application.