Repeated Averaging and Bounded Confidence Modeling, Analysis and Simulation of Continuous Opinion Dynamics
Date Issued
2007-03-05
Author(s)
Supervisors
Referees
Abstract
This thesis is about dynamical systems of agents which perform repeated averaging under bounded confidence. The main modeling issue is continuous opinion dynamics. This includes dynamics of agents in a political opinion space as well as dynamics of collective motion in swarms of mobile autonomous robots. Conditions for convergence to consensus are derived for systems where dynamics are driven by very generally defined averaging maps. Several conditions, examples and counter-examples for convergence of infinite products of row-stochastic matrices are given. Finally, the sets of fixed points are characterized. The density-based bounded confidence models are used to get an overview for the case when agents' initial opinions are uniformly distributed. Bifurcation diagrams for attractive states are computed as well as extended phase diagrams for the consensus transitions in populations with two different levels of confidence.
Subjects
social simulation
;
agent-based
;
general mean
;
density-based
;
interactive Markov chain
;
discrete master equation
;
convergence to consensus
;
infinite matrix products
;
nonnegative matrices
;
row-stochastic
;
scrambling
;
Gantmacher form
;
coefficient of ergodicity
;
averaging map
;
equiproper
;
joint spectral radius
;
sociophysics
;
bifurcation diagrams
;
extended phase diagrams
;
social psychology
Institution
Type
Dissertation
Secondary publication
No
Language
English
File(s)![Thumbnail Image]()
Loading...
Name
00010668.pdf
Size
5.83 MB
Format
Adobe PDF
Checksum
(MD5):20384fef735759e79a5f8d653e84a352