Risk measurement and risk-averse control of partially observable discrete-time Markov systems View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-10

AUTHORS

Jingnan Fan, Andrzej Ruszczyński

ABSTRACT

We consider risk measurement in controlled partially observable Markov processes in discrete time. We introduce a new concept of conditional stochastic time consistency and we derive the structure of risk measures enjoying this property. We prove that they can be represented by a collection of static law invariant risk measures on the space of function of the observable part of the state. We also derive the corresponding dynamic programming equations. Finally we illustrate the results on a machine deterioration problem. More... »

PAGES

161-184

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00186-018-0633-5

DOI

http://dx.doi.org/10.1007/s00186-018-0633-5

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https://app.dimensions.ai/details/publication/pub.1101199047


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