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On the policy improvement algorithm for ergodic risk-sensitive control

Published online by Cambridge University Press:  02 September 2020

Ari Arapostathis
Affiliation:
Department of Electrical and Computer Engineering, The University of Texas at Austin, EER 7.824, Austin, TX78712 (ari@utexas.edu)
Anup Biswas
Affiliation:
Department of Mathematics, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pune411008, India (anup@iiserpune.ac.in; somnath@iiserpune.ac.in)
Somnath Pradhan
Affiliation:
Department of Mathematics, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pune411008, India (anup@iiserpune.ac.in; somnath@iiserpune.ac.in)

Abstract

In this article we consider the ergodic risk-sensitive control problem for a large class of multidimensional controlled diffusions on the whole space. We study the minimization and maximization problems under either a blanket stability hypothesis, or a near-monotone assumption on the running cost. We establish the convergence of the policy improvement algorithm for these models. We also present a more general result concerning the region of attraction of the equilibrium of the algorithm.

Type
Research Article
Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press on behalf of The Royal Society of Edinburgh

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