A useful technique for piecewise deterministic Markov decision processes

Xin Guo, Yi Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

This note presents a technique that is useful for the study of piecewise deterministic Markov decision processes (PDMDPs) with general policies and unbounded transition intensities. This technique produces an auxiliary PDMDP from the original one. The auxiliary PDMDP possesses certain desired properties, which may not be possessed by the original PDMDP. We apply this technique to risk-sensitive PDMDPs with total cost criteria, and comment on its connection with the uniformization technique.

Original languageEnglish
Pages (from-to)55-61
Number of pages7
JournalOperations Research Letters
Volume49
Issue number1
Early online date9 Nov 2020
DOIs
Publication statusPublished - Jan 2021

Keywords

  • Continuous-time Markov decision processes
  • Piecewise deterministic Markov decision processes
  • Unbounded transition intensities

ASJC Scopus subject areas

  • Software
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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