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|Abstract:||We study information aggregation in networks where agents make binary decisions (labeled incorrect or correct). Agents initially form independent private beliefs about the better decision, which is correct with probability 1/2+δ. The dynamics we consider are asynchronous (each round, a single agent updates their announced decision) and non-Bayesian (agents simply copy the majority announcements among their neighbors, tie-breaking in favor of their private signal). Our main result proves that when the network is a tree formed according to the preferential attachment model [Barabási and Albert, 1999], with high probability, the process stabilizes in a correct majority within O(n log n/log log n) rounds. We extend our results to other tree structures, including balanced M-ary trees for any M.|
|Citation:||Bahrani, Maryam, Nicole Immorlica, Divyarthi Mohan, and S. Matthew Weinberg. "Asynchronous Majority Dynamics in Preferential Attachment Trees." In 47th International Colloquium on Automata, Languages, and Programming (ICALP) (2020): 8:1-8:14. doi:10.4230/LIPIcs.ICALP.2020.8|
|Pages:||8:1 - 8:14|
|Type of Material:||Conference Article|
|Journal/Proceeding Title:||47th International Colloquium on Automata, Languages, and Programming (ICALP)|
|Version:||Final published version. This is an open access article.|
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