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Mixing beliefs among interacting agents

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TLDR
A model of opinion dynamics in which agents adjust continuous opinions as a result of random binary encounters whenever their difference in opinion is below a given threshold is presented.
Abstract
We present a model of opinion dynamics in which agents adjust continuous opinions as a result of random binary encounters whenever their difference in opinion is below a given threshold. High thresholds yield convergence of opinions towards an average opinion, whereas low thresholds result in several opinion clusters: members of the same cluster share the same opinion but are no longer influenced by members of other clusters.

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Journal ArticleDOI

Statistical physics of social dynamics

TL;DR: In this article, a wide list of topics ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading are reviewed and connections between these problems and other, more traditional, topics of statistical physics are highlighted.
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Opinion dynamics and bounded confidence models, analysis and simulation

TL;DR: This article investigates various models for the dynamics of continuous opinions by analytical methods as well as by computer simulations for the classical model of consensus formation, a time-dependent version and a nonlinear version with bounded confidence of the agents.
BookDOI

Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms

TL;DR: This self-contained introduction to the distributed control of robotic networks offers a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation.

Distributed Control of Robotic Networks

TL;DR: This dissertation aims to provide a history of web exceptionalism from 1989 to 2002, a period chosen in order to explore its roots as well as specific cases up to and including the year in which descriptions of “Web 2.0” began to circulate.
Journal ArticleDOI

Networks beyond pairwise interactions: Structure and dynamics

TL;DR: A complete overview of the emerging field of networks beyond pairwise interactions, and focuses on novel emergent phenomena characterizing landmark dynamical processes, such as diffusion, spreading, synchronization and games, when extended beyond Pairwise interactions.
References
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Book

Introduction to percolation theory

TL;DR: In this paper, a scaling solution for the Bethe lattice is proposed for cluster numbers and a scaling assumption for cluster number scaling assumptions for cluster radius and fractal dimension is proposed.
Book

Introduction to percolation theory

TL;DR: In this article, a scaling solution for the Bethe lattice is proposed for cluster numbers and a scaling assumption for cluster number scaling assumptions for cluster radius and fractal dimension is proposed.
Journal ArticleDOI

Rational group decision making: A random field Ising model at T = 0

TL;DR: In this paper, a modified version of a finite random field Ising ferromagnetic model in an external magnetic field at zero temperature is presented to describe group decision making, where individual bias related to personal backgrounds, cultural values and past experiences are introduced via quenched local competing fields.
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