Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning

Synergistic interactions between task/resource allocation and stochastic planning exist in many environments such as transportation and logistics, UAV task assignment and disaster rescue. Existing research in exploiting these synergistic interactions between the two problems have either only conside...

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Main Authors: AGRAWAL, Pritee, Pradeep VARAKANTHAM, YEOH, William
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Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/3600
https://ink.library.smu.edu.sg/context/sis_research/article/4601/viewcontent/Scalable_greedy_algorithms_for_task.pdf
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spelling sg-smu-ink.sis_research-46012020-03-24T06:11:23Z Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning AGRAWAL, Pritee Pradeep VARAKANTHAM, YEOH, William Synergistic interactions between task/resource allocation and stochastic planning exist in many environments such as transportation and logistics, UAV task assignment and disaster rescue. Existing research in exploiting these synergistic interactions between the two problems have either only considered domains where tasks/resources are completely independent of each other or have focussed on approaches with limited scalability. In this paper, we address these two limitations by introducing a generic model for task/resource constrained multi-agent stochastic planning, referred to as TasC-MDPs. We provide two scalable greedy algorithms, one of which provides posterior quality guarantees. Finally, we illustrate the high scalability and solution performance of our approaches in comparison with existing work on two benchmark problems from the literature. 2016-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3600 https://ink.library.smu.edu.sg/context/sis_research/article/4601/viewcontent/Scalable_greedy_algorithms_for_task.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 Markov Decision Problems Multi-Agent Planning Reasoning with Uncertainty Artificial Intelligence and Robotics Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Markov Decision Problems
Multi-Agent Planning
Reasoning with Uncertainty
Artificial Intelligence and Robotics
Theory and Algorithms
spellingShingle Markov Decision Problems
Multi-Agent Planning
Reasoning with Uncertainty
Artificial Intelligence and Robotics
Theory and Algorithms
AGRAWAL, Pritee
Pradeep VARAKANTHAM,
YEOH, William
Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
description Synergistic interactions between task/resource allocation and stochastic planning exist in many environments such as transportation and logistics, UAV task assignment and disaster rescue. Existing research in exploiting these synergistic interactions between the two problems have either only considered domains where tasks/resources are completely independent of each other or have focussed on approaches with limited scalability. In this paper, we address these two limitations by introducing a generic model for task/resource constrained multi-agent stochastic planning, referred to as TasC-MDPs. We provide two scalable greedy algorithms, one of which provides posterior quality guarantees. Finally, we illustrate the high scalability and solution performance of our approaches in comparison with existing work on two benchmark problems from the literature.
format text
author AGRAWAL, Pritee
Pradeep VARAKANTHAM,
YEOH, William
author_facet AGRAWAL, Pritee
Pradeep VARAKANTHAM,
YEOH, William
author_sort AGRAWAL, Pritee
title Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
title_short Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
title_full Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
title_fullStr Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
title_full_unstemmed Scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
title_sort scalable greedy algorithms for task/resource constrained multi-agent stochastic planning
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/3600
https://ink.library.smu.edu.sg/context/sis_research/article/4601/viewcontent/Scalable_greedy_algorithms_for_task.pdf
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