markov decision processes
Markov decision processes (MDPs) are mathematical models used to solve decision-making problems in situations with uncertainty. They consist of a set of states, actions, transition probabilities, and rewards. By providing a framework to analyze sequential decision-making, MDPs enable finding the optimal strategy to maximize rewards over time, taking into account uncertain outcomes and immediate consequences of actions.
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