Abstract
AbstractA multi‐agent consensus protocol is investigated over noisy undirected connected graphs. It is supposed that each agent can know her neighbors' states with bounded noise. A theoretical stopping rule having a probabilistic guarantee is established for the consensus protocol, which explicitly relates the number of iterations with the closeness of the agreement. The stopping rule is derived by utilizing Bernstein inequality that deals with a given noise bound explicitly. The sample complexity with respect to the number of agents is also investigated, where it is shown that the number of iterations required by the proposed stopping rule based on the bound of noise itself is generally smaller than that of the conventional stopping rules that utilize bound of noise variance. The results are demonstrated through numerical examples.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
