Anthony Corso is a Ph.D. student in the Aeronautics and Astronautics Department at Stanford University where he is advised by Professor Mykel Kochenderfer in the Stanford Intelligent Systems Laboratory (SISL). He studies approaches for the validation of safety-critical autonomous systems with an emphasis on interpretability and scalability.
In this podcast he talks about safety-validation of autonomous systems. The latter includes systems such as robots, cars, aircraft, and planetary rovers equally. In May he published a paper which deals with different algorithms for black-box safety validation. One of the approaches is to use reinforcement learning, which was discussed in the podcast in more detail. He also briefly introduced the Next-Generation Airborne Collision Avoidance System ACAS X, in which development Professor Kochenderfer was heavily involved. ACAS X takes advantage of Dynamic Programming, an algorithm for optimal decision making.