Military stochastic scheduling treated as a "multi-armed bandit" problem
A Blue airborne force attacks a region defended by a single Red surface-to-air missile system (SAM). Red is uncertain about the Blues he faces, but is able to learn about them during the engagement. Red's objective is to develop a policy for shooting at the Blues to maximize the value of Blues...
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Monterey, California. Naval Postgraduate School
2001
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ftnavalpschool:oai:calhoun.nps.edu:10945/15377 2024-06-09T07:44:58+00:00 Military stochastic scheduling treated as a "multi-armed bandit" problem Glazebrook, Kevin D. Operations Research 2001-09-01 application/pdf https://hdl.handle.net/10945/15377 unknown Monterey, California. Naval Postgraduate School NPS-OR-01-010 ocn299768972 https://hdl.handle.net/10945/15377 Marine mammals Harp Baleen whales Toothed whales Technical Report 2001 ftnavalpschool 2024-05-15T00:48:21Z A Blue airborne force attacks a region defended by a single Red surface-to-air missile system (SAM). Red is uncertain about the Blues he faces, but is able to learn about them during the engagement. Red's objective is to develop a policy for shooting at the Blues to maximize the value of Blues shot down before he himself is destroyed. We show that index policies are optimal for Red in a range of scenarios and yield effective heuristics more generally. The quality of such index heuristics is confirmed in a computational study. Contract number: N00244-10-10031. Report baleen whales toothed whales Naval Postgraduate School: Calhoun |
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Naval Postgraduate School: Calhoun |
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ftnavalpschool |
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unknown |
topic |
Marine mammals Harp Baleen whales Toothed whales |
spellingShingle |
Marine mammals Harp Baleen whales Toothed whales Glazebrook, Kevin D. Military stochastic scheduling treated as a "multi-armed bandit" problem |
topic_facet |
Marine mammals Harp Baleen whales Toothed whales |
description |
A Blue airborne force attacks a region defended by a single Red surface-to-air missile system (SAM). Red is uncertain about the Blues he faces, but is able to learn about them during the engagement. Red's objective is to develop a policy for shooting at the Blues to maximize the value of Blues shot down before he himself is destroyed. We show that index policies are optimal for Red in a range of scenarios and yield effective heuristics more generally. The quality of such index heuristics is confirmed in a computational study. Contract number: N00244-10-10031. |
author2 |
Operations Research |
format |
Report |
author |
Glazebrook, Kevin D. |
author_facet |
Glazebrook, Kevin D. |
author_sort |
Glazebrook, Kevin D. |
title |
Military stochastic scheduling treated as a "multi-armed bandit" problem |
title_short |
Military stochastic scheduling treated as a "multi-armed bandit" problem |
title_full |
Military stochastic scheduling treated as a "multi-armed bandit" problem |
title_fullStr |
Military stochastic scheduling treated as a "multi-armed bandit" problem |
title_full_unstemmed |
Military stochastic scheduling treated as a "multi-armed bandit" problem |
title_sort |
military stochastic scheduling treated as a "multi-armed bandit" problem |
publisher |
Monterey, California. Naval Postgraduate School |
publishDate |
2001 |
url |
https://hdl.handle.net/10945/15377 |
genre |
baleen whales toothed whales |
genre_facet |
baleen whales toothed whales |
op_relation |
NPS-OR-01-010 ocn299768972 https://hdl.handle.net/10945/15377 |
_version_ |
1801373878142894080 |