Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments

Decentralized planning under uncertainty foragent teams is a problem of interest in manydomains including (but not limited to) disaster rescue, sensor networks and security patrolling. Decentralized MDPs, Dec-MDPs havetraditionally been used to represent such decentralized planning under uncertainty...

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Main Authors: AGRAWAL, Pritee, VARAKANTHAM, Pradeep, YEOH, William
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Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/sis_research/4251
https://ink.library.smu.edu.sg/context/sis_research/article/5254/viewcontent/342.pdf
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spelling sg-smu-ink.sis_research-52542019-01-24T09:23:42Z Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments AGRAWAL, Pritee VARAKANTHAM, Pradeep YEOH, William Decentralized planning under uncertainty foragent teams is a problem of interest in manydomains including (but not limited to) disaster rescue, sensor networks and security patrolling. Decentralized MDPs, Dec-MDPs havetraditionally been used to represent such decentralized planning under uncertainty problems.However, in many domains, agents may notbe dedicated to the team for the entire timehorizon. For instance, due to limited availability of resources, it is quite common for policepersonnel leaving patrolling teams to attend toaccidents. Such non-dedication can arise dueto the emergence of higher priority tasks ordamage to existing agents. However, there isvery limited literature dealing with handlingof non-dedication in decentralized settings. Tothat end, we provide a general model to represent problems dealing with cooperative anddecentralized planning for non-dedicated agentteams. We also provide two greedy approaches(an offline one and an offline-online one) thatare able to deal with agents leaving the teamin an effective and efficient way by exploitingthe submodularity property. Finally, we demonstrate that our approaches are able to obtainmore than 90% of optimal solution quality onbenchmark problems from the literature. 2018-09-07T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4251 https://ink.library.smu.edu.sg/context/sis_research/article/5254/viewcontent/342.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Operations and Supply Chain Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Operations and Supply Chain Management
spellingShingle Operations and Supply Chain Management
AGRAWAL, Pritee
VARAKANTHAM, Pradeep
YEOH, William
Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
description Decentralized planning under uncertainty foragent teams is a problem of interest in manydomains including (but not limited to) disaster rescue, sensor networks and security patrolling. Decentralized MDPs, Dec-MDPs havetraditionally been used to represent such decentralized planning under uncertainty problems.However, in many domains, agents may notbe dedicated to the team for the entire timehorizon. For instance, due to limited availability of resources, it is quite common for policepersonnel leaving patrolling teams to attend toaccidents. Such non-dedication can arise dueto the emergence of higher priority tasks ordamage to existing agents. However, there isvery limited literature dealing with handlingof non-dedication in decentralized settings. Tothat end, we provide a general model to represent problems dealing with cooperative anddecentralized planning for non-dedicated agentteams. We also provide two greedy approaches(an offline one and an offline-online one) thatare able to deal with agents leaving the teamin an effective and efficient way by exploitingthe submodularity property. Finally, we demonstrate that our approaches are able to obtainmore than 90% of optimal solution quality onbenchmark problems from the literature.
format text
author AGRAWAL, Pritee
VARAKANTHAM, Pradeep
YEOH, William
author_facet AGRAWAL, Pritee
VARAKANTHAM, Pradeep
YEOH, William
author_sort AGRAWAL, Pritee
title Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
title_short Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
title_full Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
title_fullStr Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
title_full_unstemmed Decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
title_sort decentralized planning for non-dedicated agent teams with submodular rewards in uncertain environments
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/sis_research/4251
https://ink.library.smu.edu.sg/context/sis_research/article/5254/viewcontent/342.pdf
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