Approximate dynamic programming using fluid and diffusion approximations with applications to power management

Wei Chen; Dayu Huang; Ankur A. Kulkarni; Jayakrishnan Unnikrishnan; Quanyan Zhu; Prashant Mehta; Sean Meyn; Adam Wierman

doi:10.1109/CDC.2009.5399685

Approximate dynamic programming using fluid and diffusion approximations with applications to power management

Wei Chen, Dayu Huang, Ankur A. Kulkarni, Jayakrishnan Unnikrishnan, Quanyan Zhu, Prashant Mehta, Sean Meyn, Adam Wierman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

TD learning and its refinements are powerful tools for approximating the solution to dynamic programming problems. However, the techniques provide the approximate solution only within a prescribed finite-dimensional function class. Thus, the question that always arises is how should the function class be chosen? The goal of this paper is to propose an approach for TD learning based on choosing the function class using the solutions to associated fluid and diffusion approximations. In order to illustrate this new approach, the paper focuses on an application to dynamic speed scaling for power management.

Original language	English (US)
Title of host publication	Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3575-3580
Number of pages	6
ISBN (Print)	9781424438716
DOIs	https://doi.org/10.1109/CDC.2009.5399685
State	Published - 2009
Event	48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China Duration: Dec 15 2009 → Dec 18 2009

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Other

Other	48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Country/Territory	China
City	Shanghai
Period	12/15/09 → 12/18/09

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Online availability

10.1109/CDC.2009.5399685

Library availability

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Chen, W., Huang, D., Kulkarni, A. A., Unnikrishnan, J., Zhu, Q., Mehta, P., Meyn, S., & Wierman, A. (2009). Approximate dynamic programming using fluid and diffusion approximations with applications to power management. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 (pp. 3575-3580). Article 5399685 (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2009.5399685

Approximate dynamic programming using fluid and diffusion approximations with applications to power management. / Chen, Wei; Huang, Dayu; Kulkarni, Ankur A. et al.
Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. Institute of Electrical and Electronics Engineers Inc., 2009. p. 3575-3580 5399685 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, W, Huang, D, Kulkarni, AA, Unnikrishnan, J, Zhu, Q, Mehta, P, Meyn, S & Wierman, A 2009, Approximate dynamic programming using fluid and diffusion approximations with applications to power management. in Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009., 5399685, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 3575-3580, 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009, Shanghai, China, 12/15/09. https://doi.org/10.1109/CDC.2009.5399685

Chen W, Huang D, Kulkarni AA, Unnikrishnan J, Zhu Q, Mehta P et al. Approximate dynamic programming using fluid and diffusion approximations with applications to power management. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. Institute of Electrical and Electronics Engineers Inc. 2009. p. 3575-3580. 5399685. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC.2009.5399685

Chen, Wei ; Huang, Dayu ; Kulkarni, Ankur A. et al. / Approximate dynamic programming using fluid and diffusion approximations with applications to power management. Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. Institute of Electrical and Electronics Engineers Inc., 2009. pp. 3575-3580 (Proceedings of the IEEE Conference on Decision and Control).

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abstract = "TD learning and its refinements are powerful tools for approximating the solution to dynamic programming problems. However, the techniques provide the approximate solution only within a prescribed finite-dimensional function class. Thus, the question that always arises is how should the function class be chosen? The goal of this paper is to propose an approach for TD learning based on choosing the function class using the solutions to associated fluid and diffusion approximations. In order to illustrate this new approach, the paper focuses on an application to dynamic speed scaling for power management.",

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AU - Chen, Wei

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AU - Zhu, Quanyan

AU - Mehta, Prashant

AU - Meyn, Sean

AU - Wierman, Adam

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AB - TD learning and its refinements are powerful tools for approximating the solution to dynamic programming problems. However, the techniques provide the approximate solution only within a prescribed finite-dimensional function class. Thus, the question that always arises is how should the function class be chosen? The goal of this paper is to propose an approach for TD learning based on choosing the function class using the solutions to associated fluid and diffusion approximations. In order to illustrate this new approach, the paper focuses on an application to dynamic speed scaling for power management.

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BT - Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009

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Approximate dynamic programming using fluid and diffusion approximations with applications to power management

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