Towards Tensor Representation of Controlled Coupled Markov Chains

For a controlled system of coupled Markov chains, which share common control parameters, a tensor description is proposed. A control optimality condition in the form of a dynamic programming equation is derived in tensor form. This condition can be reduced to a system of coupled ordinary differentia...

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Main Authors: Daniel McInnes, Boris Miller, Gregory Miller, Sergei Schreider
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/8/10/1712
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author Daniel McInnes
Boris Miller
Gregory Miller
Sergei Schreider
author_facet Daniel McInnes
Boris Miller
Gregory Miller
Sergei Schreider
author_sort Daniel McInnes
collection DOAJ
description For a controlled system of coupled Markov chains, which share common control parameters, a tensor description is proposed. A control optimality condition in the form of a dynamic programming equation is derived in tensor form. This condition can be reduced to a system of coupled ordinary differential equations and admits an effective numerical solution. As an application example, the problem of the optimal control for a system of water reservoirs with phase and balance constraints is considered.
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spelling doaj.art-e9237e7e77694272b137fc6981c2a9992023-11-20T16:05:24ZengMDPI AGMathematics2227-73902020-10-01810171210.3390/math8101712Towards Tensor Representation of Controlled Coupled Markov ChainsDaniel McInnes0Boris Miller1Gregory Miller2Sergei Schreider3School of Mathematics, Monash University, Wellington Road, Clayton VIC 3800, AustraliaSchool of Mathematics, Monash University, Wellington Road, Clayton VIC 3800, AustraliaInstitute of Informatics Problems of Federal Research Center “Computer Science and Control” RAS, 44/2 Vavilova Str., 119333 Moscow, RussiaDepartment of Management and Information Systems, Rutgers Business School, Rutgers—The State University of New Jersey, New Brunswick, NJ 07102, USAFor a controlled system of coupled Markov chains, which share common control parameters, a tensor description is proposed. A control optimality condition in the form of a dynamic programming equation is derived in tensor form. This condition can be reduced to a system of coupled ordinary differential equations and admits an effective numerical solution. As an application example, the problem of the optimal control for a system of water reservoirs with phase and balance constraints is considered.https://www.mdpi.com/2227-7390/8/10/1712coupled markov chainsstochastic controloptimal controltensor representationdynamic programming
spellingShingle Daniel McInnes
Boris Miller
Gregory Miller
Sergei Schreider
Towards Tensor Representation of Controlled Coupled Markov Chains
Mathematics
coupled markov chains
stochastic control
optimal control
tensor representation
dynamic programming
title Towards Tensor Representation of Controlled Coupled Markov Chains
title_full Towards Tensor Representation of Controlled Coupled Markov Chains
title_fullStr Towards Tensor Representation of Controlled Coupled Markov Chains
title_full_unstemmed Towards Tensor Representation of Controlled Coupled Markov Chains
title_short Towards Tensor Representation of Controlled Coupled Markov Chains
title_sort towards tensor representation of controlled coupled markov chains
topic coupled markov chains
stochastic control
optimal control
tensor representation
dynamic programming
url https://www.mdpi.com/2227-7390/8/10/1712
work_keys_str_mv AT danielmcinnes towardstensorrepresentationofcontrolledcoupledmarkovchains
AT borismiller towardstensorrepresentationofcontrolledcoupledmarkovchains
AT gregorymiller towardstensorrepresentationofcontrolledcoupledmarkovchains
AT sergeischreider towardstensorrepresentationofcontrolledcoupledmarkovchains