Faster algorithm and sharper analysis for constrained Markov decision process

The problem of constrained Markov decision process (CMDP) is investigated, where an agent aims to maximize the expected accumulated reward subject to constraints on its utilities/costs. We propose a new primal-dual approach with a novel integration of entropy regularization and Nesterov's accel...

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Vydané v:	Operations research letters Ročník 54; s. 107107
Hlavní autori:	Li, Tianjiao, Guan, Ziwei, Zou, Shaofeng, Xu, Tengyu, Liang, Yingbin, Lan, Guanghui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.05.2024
Predmet:	Accelerated gradient method Constrained Markov decision process Entropy regularization Policy optimization Primal-dual algorithm Primal-dual algorithm Constrained Markov decision process Accelerated gradient method Entropy regularization Policy optimization
ISSN:	0167-6377, 1872-7468
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