Risk Measure

Risk measures quantify the uncertainty associated with outcomes, aiming to guide decision-making under conditions of variability and potential loss. Current research focuses on developing robust and efficient methods for estimating and optimizing these measures, particularly within reinforcement learning frameworks using neural networks and algorithms like actor-critic methods and fitted-Z iteration. This work is crucial for improving the safety and reliability of autonomous systems, financial models, and other applications where risk assessment is paramount, leading to more informed and resilient decision-making processes.