1 code implementation • 7 Dec 2023 • Timothy K. Mathes, Jessica Inman, Andrés Colón, Simon Khan
Despite the impressive feats demonstrated by Reinforcement Learning (RL), these algorithms have seen little adoption in high-risk, real-world applications due to current difficulties in explaining RL agent actions and building user trust.
no code implementations • 25 Jul 2023 • Alexander Grushin, Walt Woods, Alvaro Velasquez, Simon Khan
Proxy criticality metrics that are computable in real-time (i. e., without actually simulating the effects of random actions) can be compared to the true criticality, and we show how to leverage these proxy metrics to generate safety margins, which directly tie the consequences of potentially incorrect actions to an anticipated loss in overall performance.