Markov decision processes with iterated coherent risk measures

Shanyun Chu, Yi Zhang

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


This paper considers a Markov decision process in Borel state and action spaces with the aggregated (or say iterated) coherent risk measure to be minimised. For this problem, we establish the Bellman optimality equation as well as the value and policy iteration algorithms, and show the existence of a deterministic stationary optimal policy. The cost function, while being allowed to be unbounded from below (in the sense that its negative part needs be bounded by some nonnegative real-valued possibly unbounded weight function), can be arbitrarily unbounded from above and possibly infinitely valued.

Original languageEnglish
Pages (from-to)2286-2293
Number of pages8
JournalInternational Journal of Control
Issue number11
Publication statusPublished - 2014

Bibliographical note

Publisher Copyright:
© 2014 Taylor & Francis.


  • Iterated coherent risk measure
  • Markov decision process
  • Optimality equation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications


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