Index policies for shooting problems
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Authors
Glazebrook, K.D.
Kirkbride, K.D.
Mitchell, H.M.
Gaver, D.P.
Jacobs, P.A.
Subjects
Advisors
Date of Issue
2006-01
Date
January 2006
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
We consider a scenario in which a single Red wishes to shoot at a collection of Blue targets, one at a time, to maximise some measure of return obtained from Blues killed before Red's own (possible) demise. Such a situation arises in various military contexts such as the conduct of air defence by Red in the face of Blue SEAD (suppression of enemy air defences). A class of decision processes called multi-armed bandits has been previously deployed to develop optimal policies for Red in which she attaches a calibrating (Gittins) index to each Blue target and optimally shoots next at the Blue with largest index value. The current paper seeks to elucidate how a range of developments of index theory are able to accommodate features of such problems which are of practical military import. Such features include levels of risk to Red which are policy dependent, Red having imperfect information about the Blues she faces, an evolving population of Blue targets and the possibility of Red disengagement. The paper concludes with a numerical study which both compares the performance of (optimal) index policies to a range of competitors and also demonstrates the value to Red of (optimal) disengagement.
Type
Technical Report
Description
Series/Report No
Department
Operations Research
Organization
Identifiers
NPS Report Number
NPS-OR-06-004
Sponsors
Funder
Format
ii, 24 p.: ill.;28 cm.
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.