We analyze the binary-state (either ℛ or ℬ) k-majority dynamics in a biased communication model where nodes have some fixed probability p, independent of the dynamics, of being seen in state ℬ by their neighbors. In this setting we study how p, as well as the initial unbalance between the two states, impact on the speed of convergence of the process, identifying sharp phase transitions.
@InProceedings{cruciani_et_al:LIPIcs.DISC.2020.42, author = {Cruciani, Emilio and Mimun, Hlafo Alfie and Quattropani, Matteo and Rizzo, Sara}, title = {{Brief Announcement: Phase Transitions of the k-Majority Dynamics in a Biased Communication Model}}, booktitle = {34th International Symposium on Distributed Computing (DISC 2020)}, pages = {42:1--42:3}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-168-9}, ISSN = {1868-8969}, year = {2020}, volume = {179}, editor = {Attiya, Hagit}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2020.42}, URN = {urn:nbn:de:0030-drops-131200}, doi = {10.4230/LIPIcs.DISC.2020.42}, annote = {Keywords: Biased Communication, Consensus, Majority Dynamics, Markov Chains, Metastability} }
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