@conference {
	title = {Performance Evaluation of Multi-Agent Distributed Collaborative Optimizationunder Random Communication Topologies},
	author = {Matei, Ion., Baras, John S.},
	year = {2010},
	month = {07/2010},
	abstract = {We investigate collaborative optimization in a multi-agent setting, when the agents execute in a distributed manner using local information, while the communication topology used to exchange messages and information is modeled by a graph-valued random process, independent of other time instances. Specifically, we study the performance of the consensus-based multi-agent subgradient method, for the case of a constant stepsize, as measured by two metrics: rate of convergence and guaranteed region of convergence, evaluated via their expected values. Under a strong convexity type of assumption, we provide upper bounds on the performance metrics, which explicitly depend on the probability distribution of the random graph and on the agents{\textquoteright} estimates of the optimal solution. This provides a guide for tuning the parameters of the communication protocol such that good performance of the multi-agent subgradient method is ensured.},
	address = {Budapest, Hungary},
	booktitle = {Proceedings of the19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)},
	pages = {pp.1-8}
}
