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It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision ...
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Partially observable Markov decision process - Wikipedia
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A partially observable Markov decision process (POMDP) is a generalization of a Markov decision process (MDP). A POMDP models an agent decision process in ...
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A Markov decision process is a method for optimizing decision making over time in a step-by-step manner in situations where the outcomes of the decisions ...
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A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the ...
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In probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only on ...
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The decentralized partially observable Markov decision process (Dec-POMDP) is a model for coordination and decision-making among multiple agents.
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The main article for this category is Markov process. This category is for articles about the theory of Markov chains and processes, and associated processes.
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This article contains examples of Markov chains and Markov processes in action. All examples are in the countable state space. For an overview of Markov ...
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