DocumentCode :
3536843
Title :
On indigenous random consensus and averaging dynamics
Author :
Touri, Behrouz ; Langbort, Cedric
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Tech Univ., Atlanta, GA, USA
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
6208
Lastpage :
6212
Abstract :
We study indigenously evolving random averaging dynamics, i.e., random averaging dynamics whose evolution depends on the history of the random dynamics itself. Such dynamical processes find applications in, e.g., models of distributed learning of comparative adjectives in Linguistics, asymmetric state-dependent random gossiping in Computer Science, Hegselmann-Krause opinion dynamics with link-failure and/or random observation radius in Social Sciences, to name just a few. We introduce a novel supermartingale technique to analyze such history-dependent random dynamics. Using this new tool, we show that an adapted random averaging dynamics converges under general conditions and provide a characterization for the asymptotic behavior of such dynamics.
Keywords :
mobile robots; random processes; robot dynamics; Hegselmann-Krause opinion dynamics; asymmetric state-dependent random gossiping; asymptotic behavior; computer science; distributed learning model; dynamical processes; history-dependent random dynamics; indigenous random consensus; linguistics; link-failure; random averaging dynamics; random observation radius; robotic network; social sciences; supermartingale technique; Aerodynamics; Conferences; Convergence; Heuristic algorithms; History; Signal processing algorithms; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6760870
Filename :
6760870
Link To Document :
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