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Risk sensitive control of Markov processes in countable state space

✍ Scribed by Daniel Hernandez-Hernández; Steven I. Marcus

Publisher
Elsevier Science
Year
1996
Tongue
English
Weight
450 KB
Volume
29
Category
Article
ISSN
0167-6911

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✦ Synopsis

In this paper we consider infinite horizon risk-sensitive control of Markov processes with discrete time and denumerable state space. This problem is solved by proving, under suitable conditions, that there exists a bounded solution to the dynamic programming equation. The dynamic programming equation is transformed into an Isaacs equation for a stochastic game, and the vanishing discount method is used to study its solution. In addition, we prove that the existence conditions are also necessary.

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