MDP Applications

Markov Decision Processes (MDPs) are mathematical frameworks used to model decision-making scenarios where outcomes are partly random and partly under the control of a decision-maker. They help in designing optimal strategies in areas like robotics, finance, healthcare, and supply chain management by analyzing possible actions, predicting future states, and maximizing rewards or minimizing costs over time. Essentially, MDPs provide a structured way to make the best choices in complex, uncertain environments, enabling systems to learn and adapt to achieve desired goals efficiently.