The performance of forwards induction policies

K. D. Glazebrook and J. C. Gittins

Stochastic Processes and their Applications, 1993, vol. 46, issue 2, 301-326

Abstract: Following major theoretical advances in the study of multi-armed bandit problems, Gittins proposed a forwards induction (FI) approach to the development of policies for Markov decision processes (MDP's). Considerable computational savings are often possible over conventional dynamic programming. We describe procedures for computing such policies and give a bound on their suboptimality. This yields, inter alia, a probabilistic analysis of FI policies for families of competing MDP's. The paper concludes with a detailed study of the status of FI policies for stochastic scheduling problems with order constraints.

Keywords: dynamic; programming; forward; induction; Gittins; index; Markov; decision; process; stochastic; scheduling (search for similar items in EconPapers)
Date: 1993
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(93)90009-S
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:46:y:1993:i:2:p:301-326

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().