A Markov Decision Process (MDP) is a mathematical framework used for modeling decision-making situations where outcomes are partly random and partly under the control of a decision maker. MDPs provide a structured way to formulate problems involving states, actions, rewards, and transitions, allowing for optimal decision-making over time. They are particularly important in the development of decision-making algorithms as they enable agents to evaluate various strategies based on expected future rewards.
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