Cooperative Control and Potential Games

J. R. Marden; G. Arslan; J. S. Shamma

doi:10.1109/TSMCB.2009.2017273

Cooperative Control and Potential Games

J. R. Marden^*, G. Arslan, J. S. Shamma

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

430 Scopus citations

Abstract

We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these settings. Motivated by this connection, we build upon game-theoretic concepts to better accommodate a broader class of cooperative control problems. In particular, we extend existing learning algorithms to accommodate restricted action sets caused by the limitations of agent capabilities and group-based decision making. Furthermore, we also introduce a new class of games called sometimes weakly acyclic games for time-varying objective functions and action sets, and provide distributed algorithms for convergence to an equilibrium.

Original language	English (US)
Pages (from-to)	1393-1407
Number of pages	15
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume	39
Issue number	6
DOIs	https://doi.org/10.1109/TSMCB.2009.2017273
State	Published - 2009
Externally published	Yes

Keywords

Cooperative control
Cooperative systems
Game theory
Learning
Learning in games
Multi-agent systems
Multiagent systems

ASJC Scopus subject areas

Control and Systems Engineering
Software
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TSMCB.2009.2017273

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@article{10bace545ac44e38bfcb611595ea6641,

title = "Cooperative Control and Potential Games",

abstract = "We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these settings. Motivated by this connection, we build upon game-theoretic concepts to better accommodate a broader class of cooperative control problems. In particular, we extend existing learning algorithms to accommodate restricted action sets caused by the limitations of agent capabilities and group-based decision making. Furthermore, we also introduce a new class of games called sometimes weakly acyclic games for time-varying objective functions and action sets, and provide distributed algorithms for convergence to an equilibrium.",

keywords = "Cooperative control, Cooperative systems, Game theory, Learning, Learning in games, Multi-agent systems, Multiagent systems",

author = "Marden, {J. R.} and G. Arslan and Shamma, {J. S.}",

note = "Funding Information: Manuscript received September 16, 2008; revised January 28, 2009. First published April 14, 2009; current version published November 18, 2009. This work was supported in part by the Social and Information Sciences Laboratory, California Institute of Technology, by the Army Research Office under Grant W911NF04316, by the Air Force Office of Scientific Research under Grant FA9550-08-1-0375, and by the National Science Foundation under Grant ECS-0501394 and Grant ECCS-0547692. This paper was recommended by Associate Editor T. Vasilakos. Funding Information: Dr. Arslan was the recipient of the National Science Foundation CAREER Award in May 2006.",

year = "2009",

doi = "10.1109/TSMCB.2009.2017273",

language = "English (US)",

volume = "39",

pages = "1393--1407",

journal = "IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics",

issn = "1083-4419",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "6",

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AU - Marden, J. R.

AU - Arslan, G.

AU - Shamma, J. S.

N1 - Funding Information: Manuscript received September 16, 2008; revised January 28, 2009. First published April 14, 2009; current version published November 18, 2009. This work was supported in part by the Social and Information Sciences Laboratory, California Institute of Technology, by the Army Research Office under Grant W911NF04316, by the Air Force Office of Scientific Research under Grant FA9550-08-1-0375, and by the National Science Foundation under Grant ECS-0501394 and Grant ECCS-0547692. This paper was recommended by Associate Editor T. Vasilakos. Funding Information: Dr. Arslan was the recipient of the National Science Foundation CAREER Award in May 2006.

PY - 2009

Y1 - 2009

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AB - We present a view of cooperative control using the language of learning in games. We review the game-theoretic concepts of potential and weakly acyclic games, and demonstrate how several cooperative control problems, such as consensus and dynamic sensor coverage, can be formulated in these settings. Motivated by this connection, we build upon game-theoretic concepts to better accommodate a broader class of cooperative control problems. In particular, we extend existing learning algorithms to accommodate restricted action sets caused by the limitations of agent capabilities and group-based decision making. Furthermore, we also introduce a new class of games called sometimes weakly acyclic games for time-varying objective functions and action sets, and provide distributed algorithms for convergence to an equilibrium.

KW - Cooperative control

KW - Cooperative systems

KW - Game theory

KW - Learning

KW - Learning in games

KW - Multi-agent systems

KW - Multiagent systems

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DO - 10.1109/TSMCB.2009.2017273

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SN - 1083-4419

VL - 39

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JO - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

JF - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

IS - 6

ER -

Cooperative Control and Potential Games

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Keywords

ASJC Scopus subject areas

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