Markov Decision Process

A mathematical framework for modeling sequential decision-making problems where outcomes are partly random and partly under the control of a decision-maker. MDPs define the environment in which a reinforcement learning agent operates, specifying states, actions, transition probabilities, and rewards, and provide the theoretical foundation for most RL algorithms.