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Proceedings of the 40th IEEE Conference on Decision and Control Orlando, Florida USA, December 2001 WeM13-4

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Markov decision processes (MDPs) are a mathematical framework used to model decision-making situations where outcomes are partially random and partially under the control of a decision-maker.

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There is no specific requirement to file MDPs as they are a modeling and analysis tool used in the field of artificial intelligence and decision theory.

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MDPs are mathematical models that can be constructed and analyzed using algorithms and computational methods. There is no specific form or template for filling out MDPs.

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The purpose of MDPs is to help decision-makers determine the optimal actions to take in a given situation, considering the uncertain outcomes and the long-term consequences of their decisions.

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There is no specific information that needs to be reported on MDPs. The model itself represents the decision-making process and the probabilities of different outcomes.

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