A Potential-Game Approach for Information-Maximizing Cooperative Planning of Sensor Networks

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This paper presents a potential-game approach for distributed cooperative selection of informative sensors, when the goal is to maximize the mutual information between the measurement variables and the quantities of interest. It is proved that a local utility function defined by the conditional mutual information of an agent conditioned on the other agents' sensing decisions leads to a potential game, with the global potential being the original mutual information of the cooperative planning problem. The joint strategy fictitious play method is then applied to obtain a distributed solution that provably converges to a pure strategy Nash equilibrium. Two illustrative numerical examples are presented to demonstrate good convergence and performance properties of the proposed game-theoretic method.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2015-11
Language
English
Article Type
Article
Citation

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, v.23, no.6, pp.2326 - 2335

ISSN
1063-6536
DOI
10.1109/TCST.2015.2403475
URI
http://hdl.handle.net/10203/205185
Appears in Collection
AE-Journal Papers(저널논문)
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