Abstract
Motivated by various random variations of the Hegselmann-Krause model for opinion dynamics and gossip algorithm in an endogenously changing environment, we propose a general framework for the study of endogenously varying random averaging dynamics, that is, averaging dynamics whose evolution suffers from history-dependent sources of randomness. We show that under general assumptions, such dynamics is convergent almost surely. We also determine the limiting behavior and show that infinitely many time-varying Lyapunov functions are admitted.
| Original language | English (US) |
|---|---|
| Article number | 6851878 |
| Pages (from-to) | 241-248 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Control of Network Systems |
| Volume | 1 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 1 2014 |
Keywords
- Stochastic systems
- complex networks
- distributed computing
- distributed control
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications
- Control and Optimization