Markov decision process
In mathematics, a Markov decision process (MDP) is a discrete-time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying optimization problems solved via dynamic programming. MDPs were known at least as early as the 1950s; a core body of research on Markov decision processes resulted from Ronald Howard's 1960 book, Dynamic Programming and Markov Processes. They are used in many disciplines, including robotics, automatic control, economics and manufacturing. The name of MDPs comes from the Russian mathematician Andrey Markov as they are an extension of Markov chains.
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Algorithms for solving Markov decision processesAndrey MarkovApprenticeship learningArtificial neural networkAutomated planning and schedulingAutomatic basis function constructionBellman equationBulk queueCatalog of articles in probability theoryCollaborative filteringComputational tools for artificial intelligenceCyrus DermanDecentralized partially observable Markov decision processDeep reinforcement learningDialog managerDiffusion waveletsDirected informationDiscrete Poisson equationDrift plus penaltyDynamic discrete choiceDynamic programmingGame theoryGenerative modelGijsbert de LeveGittins indexGlossary of artificial intelligenceGraph isomorphism problemIntrinsic motivation (artificial intelligence)Ionescu-Tulcea theoremKeith W. RossLearning automatonList of acronyms: MList of algorithmsList of numerical analysis topicsList of statistics articlesList of things named after Andrey MarkovMDPMachine learningMark E. Lewis (engineer)Markov Decision Process
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Markov decision process
In mathematics, a Markov decision process (MDP) is a discrete-time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying optimization problems solved via dynamic programming. MDPs were known at least as early as the 1950s; a core body of research on Markov decision processes resulted from Ronald Howard's 1960 book, Dynamic Programming and Markov Processes. They are used in many disciplines, including robotics, automatic control, economics and manufacturing. The name of MDPs comes from the Russian mathematician Andrey Markov as they are an extension of Markov chains.
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En théorie de la décision et d ...... vien est une chaîne de Markov.
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I processi decisionali di Mark ...... orzo (reinforcement learning).
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In mathematics, a Markov decis ...... ess reduces to a Markov chain.
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Markovovy rozhodovací procesy ...... redukoval na Markovův řetězec.
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Ма́рковські проце́си вирі́шува ...... иться до марковського ланцюга.
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Марковский процесс принятия ре ...... ние, экономику и производство.
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عملية ماركوف (بالإنجليزية: Mar ...... المتقطع مقابل الزمن المتواصل.
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マルコフ決定過程(マルコフけっていかてい、英: Markov ...... や自動制御、経済学、製造業を含む幅広い分野で用いられている。
@ja
在數學中,馬可夫決策過程(MDP)是隨機控製過程。 它提供了 ...... 前的狀態和動作; 換句話說,MDP的狀態轉換滿足馬可夫性質。
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July 2018
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The derivation of the substituion is needed
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En théorie de la décision et d ...... et l'industrie manufacturière.
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I processi decisionali di Mark ...... , e la produzione industriale.
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In mathematics, a Markov decis ...... an extension of Markov chains.
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Markovovy rozhodovací procesy ...... ekonomie a průmyslové výroby.
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Ма́рковські проце́си вирі́шува ...... м, економікою та виробництвом.
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Марковский процесс принятия ре ...... ние, экономику и производство.
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عملية ماركوف (بالإنجليزية: Mar ...... المتقطع مقابل الزمن المتواصل.
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マルコフ決定過程(マルコフけっていかてい、英: Markov ...... や自動制御、経済学、製造業を含む幅広い分野で用いられている。
@ja
在數學中,馬可夫決策過程(MDP)是隨機控製過程。 它提供了 ...... 前的狀態和動作; 換句話說,MDP的狀態轉換滿足馬可夫性質。
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label
Markov decision process
@en
Markovův rozhodovací proces
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Markow-Entscheidungsproblem
@de
Processo decisionale di Markov
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Processus de décision markovien
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Марковский процесс принятия решений
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Марковський процес вирішування
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قرارات عملية ماركوف
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マルコフ決定過程
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馬可夫決策過程
@zh