A Stopping Rule for Multi-Agent Consensus over Unbalanced Noisy Networks

Abstract

A stochastic weighted averaging consensus algorithm is considered for a multi-agent system over a noisy unbalanced directed network. The convergence of the algorithm is investigated, which gives an explicit relation between the number of iterations and the closeness of the agreement, i.e., a stopping rule.