Title :
Stochastic approximation for consensus seeking: Mean square and almost sure convergence
Author :
Huang, Minyi ; Manton, Jonathan H.
Author_Institution :
Carleton Univ., Ottawa
Abstract :
We consider stochastic consensus problems in strongly connected directed graph models where each agent has noisy measurements of its neighbors´ states. For consensus seeking, we develop stochastic approximation type algorithms with a decreasing step size and establish mean square and almost sure convergence of the agents´ states to the same limit.
Keywords :
convergence; directed graphs; mean square error methods; multi-agent systems; stochastic processes; almost sure convergence; consensus seeking; directed graph models; mean square; stochastic approximation; stochastic consensus problems; Approximation algorithms; Control systems; Convergence; Fading; Laplace equations; Quantization; Stochastic processes; Stochastic resonance; USA Councils; Wireless sensor networks;
Conference_Titel :
Decision and Control, 2007 46th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-1497-0
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2007.4434630
