The Annals of Statistics

Adaptive Policies for Markov Renewal Programs

Bennett L. Fox and John E. Rolph

Full-text: Open access

Abstract

We recast a class of denumerable-state, infinite-action Markov renewal programs with unknown parameters as one-state programs with actions corresponding to stationary policies in the original program. Under suitable conditions we find an adaptive (nonstationary) optimal policy in the sense of maximizing long-run expected reward per unit time.

Article information

Source
Ann. Statist., Volume 1, Number 2 (1973), 334-341.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176342370

Digital Object Identifier
doi:10.1214/aos/1176342370

Mathematical Reviews number (MathSciNet)
MR351430

Zentralblatt MATH identifier
0259.90056

JSTOR
links.jstor.org

Citation

Fox, Bennett L.; Rolph, John E. Adaptive Policies for Markov Renewal Programs. Ann. Statist. 1 (1973), no. 2, 334--341. doi:10.1214/aos/1176342370. https://projecteuclid.org/euclid.aos/1176342370


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