Adaptive control of Markov processes with incomplete state information and unknown parameters
type: Item
instance of: scholarly article
title: Adaptive control of Markov processes with incomplete state information and unknown parameters
zbMATH Open document ID: 0585.90090
DOI: 10.1007/BF00941283
author: Onésimo Hernández-Lerma
author: Steven I. Marcus
published in: Journal of Optimization Theory and Applications
publication date: 1987-01-01T00:00:00Z
review text: Recent results for parameter-adaptive Markov decision processes (MDP's) are extended to partially observed MDP's depending on unknown parameters. These results include approximations converging uniformly to the optimal reward function and asymptotically optimal adaptive policies.
Mathematics Subject Classification ID: 90C40
zbMATH DE Number: 3939122
zbMATH Keywords: unknown parameters
zbMATH Keywords: approximations
zbMATH Keywords: optimal reward function
zbMATH Keywords: asymptotically optimal adaptive policies
zbMATH Keywords: partially observed Markov decision processes
zbMATH Keywords: discounted reward criterion
zbMATH Keywords: nonstationary value iteration
zbMATH Keywords: principle of estimation and control
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 3939122