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As the complexity of power plants increase, so does the difficulty in accurately modeling the interactions among the subsystems. Distributed sensing and control offers a possible solution to this problem, but introduces a new one: how to ensure that each subsystem satisfying its control objective leads to the safe and reliable operation of the entire power plant.In this work we present a distributed coordination algorithm that offers safe, reliable, and scalable control of a distributed system. In this approach, each system component uses a reinforcement learning algorithms to achieve its own objectives, but those objectives are derived to coordinate implicitly and achieve the system level objective. We show that in a Time-Extended Defect Combination Problem where the agents need to determine when and whether or not they should be sensing in order to maintain QoS in a system, the proposed method outperforms traditional methods by up to two orders of magnitude.
(unavailable)
@incollection{tumer-colby_fiiw12,
author = {M. Colby and C. Holmes Parker and K. Tumer},
title = {Coordination and Control for Large Distributed Sensor Networks},
booktitle = {Future of Instrumentation International Workshop (FIIW-2012)},
month = {October},
address = {Gatlinburg, TN},
editors = {K. Tobin Jr.},
abstract={As the complexity of power plants increase, so does the difficulty in accurately modeling the interactions among the subsystems. Distributed sensing and control offers a possible solution to this problem, but introduces a new one: how to ensure that each subsystem satisfying its control objective leads to the safe and reliable operation of the entire power plant.
In this work we present a distributed coordination algorithm that offers safe, reliable, and scalable control of a distributed system. In this approach, each system component uses a reinforcement learning algorithms to achieve its own objectives, but those objectives are derived to coordinate implicitly and achieve the system level objective. We show that in a Time-Extended Defect Combination Problem where the agents need to determine when and whether or not they should be sensing in order to maintain QoS in a system, the proposed method outperforms traditional methods by up to two orders of magnitude.},
bib2html_pubtype = {Workshop/Symposium Papers},
bib2html_rescat = {Multiagent Systems, Complex Systems},
year = {2012}
}
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