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Markov Decision Processes with Average-Value-at-Risk criteria

Bäuerle, N.; Ott, J.

We investigate the problem of minimizing the Average-Value-at-Risk (AV aRr) of the discounted cost over a finite and an infinite horizon which is generated by a Markov Decision Process (MDP). We show that this problem can be reduced to an ordinary MDP with extended state space and give conditions under which an optimal policy exists. We also give a time-consistent interpretation of the AV aRr . At the end we consider a numerical example which is a simple repeated casino game. It is used to discuss the influence of the risk aversion parameter r of the AV aRr-criterion.

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DOI: 10.5445/IR/1000032887
DOI: 10.1007/s00186-011-0367-0
Zitationen: 26
Web of Science
Zitationen: 21
Zugehörige Institution(en) am KIT Institut für Stochastik (STOCH)
Publikationstyp Zeitschriftenaufsatz
Jahr 2011
Sprache Englisch
Identifikator ISSN: 1432-2994
KITopen-ID: 1000032887
Erschienen in Mathematical Methods of Operations Research
Band 74
Heft 3
Seiten 361-379
Schlagworte Markov Decision Problem, Average-Value-at-Risk, Time-consistency, Risk aversion
Nachgewiesen in Web of Science
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