DISTRIBUTED CORRELATED Q-LEARNING FOR DYNAMIC TRANSMISSION CONTROL OF SENSOR NETWORKS

被引：5
|
作者：
Huang, Jane Wei [1 ]
Zhu, Quanyan [2 ]
Krishnamurthy, Vikram [1 ]
Basar, Tamer [2 ]
机构：
[1] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V5Z 1M9, Canada
[2] Univ Illinois, Dept Elect & Comp Engn, Urbana, IL USA
来源：
2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2010年
关键词：
Game Theory; Distributed Algorithms; Multisensor Systems; Stochastic games; EQUILIBRIUM;
D O I：
10.1109/ICASSP.2010.5495265
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
This paper considers a Markovian dynamical game theoretic setting for distributed transmission control in a wireless sensor network. The available spectrum bandwidth is modeled as a Markov chain. A distributed algorithm named correlated Q-learning algorithm is proposed to obtain the correlated equilibrium policies of the system. This algorithm has the decentralized feature and is easily implementable in a real system. Numerical example is also provided to verify the performances of the proposed algorithms.
引用
收藏
页码：1982 / 1985
页数：4
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