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A stopping rule is presented for a multiagent consensus algorithm with noisy communication. A stochastic approximation method is employed and the relation between the closeness of the agreement and the number of iterations is established. A bound of the variation of the agents at the specific number of iterations is then derived with a probabilistic guarantee, which gives a rigorous stopping rule...
A stochastic approximation with averaging is applied to a consensus algorithm for multi-agent systems and the convergence of the algorithm is analyzed. The consensus is considered with respect to the time average of the states of agents. For the fixed network structure and time-varying structure, the relation between the number of iterations of the algorithm and consensus accuracy is explicitly clarified...
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