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Title: Risk probability optimization problem for finite horizon continuous time Markov decision processes with loss rate (English)
Author: Huo, Haifeng
Author: Wen, Xian
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 57
Issue: 2
Year: 2021
Pages: 272-294
Summary lang: English
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Category: math
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Summary: This paper presents a study the risk probability optimality for finite horizon continuous-time Markov decision process with loss rate and unbounded transition rates. Under drift condition, which is slightly weaker than the regular condition, as detailed in existing literature on the risk probability optimality Semi-Markov decision processes, we prove that the value function is the unique solution of the corresponding optimality equation, and demonstrate the existence of a risk probability optimization policy using an iteration technique. Furthermore, we provide verification of the imposed condition with two examples of controlled birth-and-death system and risk control, and further demonstrate that a value iteration algorithm can be used to calculate the value function and develop an optimal policy. (English)
Keyword: continuous-time Markov decision processes
Keyword: loss rate
Keyword: risk probability criterion
Keyword: finite horizon
Keyword: optimal policy
Keyword: unbounded transition rate
MSC: 60E20
MSC: 90C40
idZBL: Zbl 07396267
idMR: MR4273576
DOI: 10.14736/kyb-2021-2-0272
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Date available: 2021-07-30T13:08:05Z
Last updated: 2021-11-01
Stable URL: http://hdl.handle.net/10338.dmlcz/149039
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