In linear models of consensus dynamics, the state of the various agents converges to a value which is a convex combination of the agents' initial states. We call it democratic if in the large scale limit (number of agents going to infinity) the vector of convex weights converges to 0 uniformly. Democracy is a relevant property which naturally shows up when we deal with opinion dynamic models and cooperative algorithms such as consensus over a network: it says that each agent's measure/opinion is going to play a negligeable role in the asymptotic behavior of the global system. It can be seen as a relaxation of average consensus, where all agents have exactly the same weight in the final value, which becomes negligible for a large number of agents.
The robustness of democratic consensus / Fagnani, Fabio; Delvenne, J. C.. - In: AUTOMATICA. - ISSN 0005-1098. - STAMPA. - 52(2015), pp. 232-241. [10.1016/j.automatica.2014.12.001]
|Titolo:||The robustness of democratic consensus|
|Data di pubblicazione:||2015|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.automatica.2014.12.001|
|Appare nelle tipologie:||1.1 Articolo in rivista|