Continuous-Time Markov Decision Processes Under the Risk-Sensitive First Passage Discounted Cost Criterion
Qingda Wei () and
Xian Chen ()
Additional contact information
Qingda Wei: Huaqiao University
Xian Chen: Xiamen University
Journal of Optimization Theory and Applications, 2023, vol. 197, issue 1, No 12, 309-333
Abstract:
Abstract This paper studies the risk-sensitive first passage discounted cost criterion for continuous-time Markov decision processes with the Borel state and action spaces. The cost and transition rates are allowed to be unbounded. We introduce a new value iteration to establish the existence of a solution to the risk-sensitive first passage discounted cost optimality equation. Then applying the Feynman–Kac formula, we show that the risk-sensitive first passage discounted cost optimal value function is a unique solution to the risk-sensitive first passage discounted cost optimality equation. Moreover, we derive the existence of a deterministic Markov optimal policy in the class of randomized history-dependent policies. Finally, a cash flow model is given to illustrate the results.
Keywords: Continuous-time Markov decision processes; Risk-sensitive first passage discounted cost criterion; Optimal policies; Value iteration.; 90C40; 60J27 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10957-023-02179-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:197:y:2023:i:1:d:10.1007_s10957-023-02179-3
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-023-02179-3
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().