Stochastic Control Theory

Stochastic Control Theory is a mathematical framework for making decisions in systems influenced by randomness and uncertainty. It involves choosing optimal strategies or control actions to guide a system's behavior over time, despite unpredictable factors. This theory models real-world scenarios—like finance, robotics, or economics—where outcomes are uncertain, aiming to balance risk and reward by dynamically adjusting controls based on current information. Essentially, it helps find the best possible way to steer a system toward desired goals when future events cannot be precisely predicted.