Deterministic policy gradient algorithms for semi‐Markov decision processes

A large class of sequential decision‐making problems under uncertainty, with broad applications from preventive maintenance to event‐triggered control can be modeled in the framework of semi‐Markov decision processes (SMDPs). Unlike Markov decision processes (MDPs), SMDPs are underexplored in the on...

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Vydané v:	International journal of intelligent systems Ročník 37; číslo 7; s. 4008 - 4019
Hlavní autori:	Hosseinloo, Ashkan Haji, Dahleh, Munther A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York John Wiley & Sons, Inc 01.07.2022
Predmet:	Algorithms average reward deterministic policy Intelligent systems Markov analysis Markov processes policy gradient theorem Preventive maintenance reinforcement learning SMDP Theorems
ISSN:	0884-8173, 1098-111X
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