Stopping Time

Stopping time, the moment a process concludes, is a crucial concept across diverse fields, with current research focusing on optimizing its determination under various constraints. Researchers are developing algorithms, including reinforcement learning and linear programming approaches, to find optimal stopping times while satisfying safety or privacy conditions, often within frameworks like Markov decision processes or differential inclusions. These advancements have implications for areas such as safe reinforcement learning, sequential inference, and personalized recommendations, enabling more efficient and responsible decision-making in complex systems.