Asymptotic expansions for dynamic programming recursions with general nonnegative matrices

Abstract

This paper is concerned with the study of the asymptotic behavior of dynamic programming recursions of the form $$x(n + 1) = \mathop {\max }\limits_{P \in \mathcal{K}} Px(n), n = 0,1,2,...,$$ where ℜ denotes a set of matrices, generated by all possible interchanges of corresponding rows, taken from a fixed finite set of nonnegative square matrices. These recursions arise in a number of well-known and frequently studied problems, e.g. in the theory of controlled Markov chains, Leontief substitution systems, controlled branching processes, etc. Results concerning the asymptotic behavior ofx(n), forn→∞, are established in terms of the maximal spectral radius, the maximal index, and a set of generalized eigenvectors. A key role in the analysis is played by a geometric convergence result for value iteration in undiscounted multichain Markov decision processes. A new proof of this result is also presented.