Abstract

This paper presents a successive approximation method for solving systems of nested functional equations which arise, e.g., when considering Markov renewal programs in which policies that are maximal gain or optimal under more selective discount — and average overtaking optimality criteria are to be found. In particular, a successive approximation method is given to find the optimal bias vector and bias-optimal policies. Applications with respect to a number of additional stochastic control models are pointed out.

Our method is based on systems of simultaneously generated (single-equation) value-iteration schemes.

Authors
Awi Federgruen and Paul Schweitzer
Format
Journal Article
Publication Date
Journal
Mathematics of Operations Research

Full Citation

Federgruen, Awi and Paul Schweitzer
. “Successive approximation methods for solving nested functional equations in Markov decision problems.”
Mathematics of Operations Research
vol.
9
, (August 01, 1984):
319
-
344
.