Generative AI and Stochastic Optimal Control and Reinforcement Learning Frameworks for Adaptive and Intelligent Decision-Making Systems
Sequential decision-making under uncertainty has traditionally been formalized through two largely separate mathematical traditions: stochastic optimal control, which derives policies from explicit dynamics models and value functions, and reinforcement learning (RL), which learns policies directly from interaction with...