Average optimality for risk-sensitive control with general state space
Risk Management
2016-08-14 v1 Probability
Abstract
This paper deals with discrete-time Markov control processes on a general state space. A long-run risk-sensitive average cost criterion is used as a performance measure. The one-step cost function is nonnegative and possibly unbounded. Using the vanishing discount factor approach, the optimality inequality and an optimal stationary strategy for the decision maker are established.
Keywords
Cite
@article{arxiv.0704.0394,
title = {Average optimality for risk-sensitive control with general state space},
author = {Anna Jaśkiewicz},
journal= {arXiv preprint arXiv:0704.0394},
year = {2016}
}
Comments
Published at http://dx.doi.org/10.1214/105051606000000790 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)