Distributed subgradient method for multi-agent optimization with quantized communication
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- 作者：Jueyou Li ; Guo Chen ; Zhiyou Wu and Xing He
- 刊名：Mathematical Methods in the Applied Sciences
- 出版年：2017
- 出版时间：15 March 2017
- 年：2017
- 卷：40
- 期：4
- 页码：1201-1213
- 全文大小：468K
- ISSN：1099-1476
文摘
This paper focuses on a distributed optimization problem associated with a time-varying multi-agent network with quantized communication, where each agent has local access to its convex objective function, and cooperatively minimizes a sum of convex objective functions of the agents over the network. Based on subgradient methods, we propose a distributed algorithm to solve this problem under the additional constraint that agents can only communicate quantized information through the network. We consider two kinds of quantizers and analyze the quantization effects on the convergence of the algorithm. Furthermore, we provide explicit error bounds on the convergence rates that highlight the dependence on the quantization levels. Finally, some simulation results on a l1-regression problem are presented to demonstrate the performance of the algorithm. Copyright