Abstract
We study bounded confidence opinion dynamics on graphs. At each iteration, agents average their opinions with those of their neighbors in the graph who have similar opinions. We show that these dynamics converge and study the limiting values. Then we propose and study a variation, called localized distributed averaging, which targets applications where nodes' opinions or measurements are only useful to other nearby nodes. The utility of localized distributed averaging is illustrated through a source localization example in wireless sensor networks.
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.
