Consensus in opinion dynamics as a repeated game

Dario Bauso; Mark Cannon

doi:10.1016/j.automatica.2017.12.062

Consensus in opinion dynamics as a repeated game

Dario Bauso^*, Mark Cannon

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

29 Citations (Scopus)

113 Downloads (Pure)

Abstract

We study an n-agent averaging process with dynamics subject to controls and adversarial disturbances. The model arises in multi-population opinion dynamics with macroscopic and microscopic intertwined dynamics. The averaging process describes the influence from neighbouring populations, whereas the input term indicates how the distribution of opinions in the population changes as a result of dynamical evolutions at a microscopic level (individuals' changing opinions). The input term is obtained as the vector payoff of a two player repeated game. We study conditions under which the agents achieve robust consensus to some predefined target set. Such conditions build upon the approachability principle in repeated games with vector payoffs. (C) 2018 Elsevier Ltd. All rights reserved.

Original language	English
Pages (from-to)	204-211
Number of pages	8
Journal	Automatica
Volume	90
DOIs	https://doi.org/10.1016/j.automatica.2017.12.062
Publication status	Published - Apr-2018
Externally published	Yes

Keywords

Game theory
Networks
Allocations
Robust receding horizon control
NETWORKED MULTIAGENT SYSTEMS
MODEL

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AU - Bauso, Dario

AU - Cannon, Mark

PY - 2018/4

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AB - We study an n-agent averaging process with dynamics subject to controls and adversarial disturbances. The model arises in multi-population opinion dynamics with macroscopic and microscopic intertwined dynamics. The averaging process describes the influence from neighbouring populations, whereas the input term indicates how the distribution of opinions in the population changes as a result of dynamical evolutions at a microscopic level (individuals' changing opinions). The input term is obtained as the vector payoff of a two player repeated game. We study conditions under which the agents achieve robust consensus to some predefined target set. Such conditions build upon the approachability principle in repeated games with vector payoffs. (C) 2018 Elsevier Ltd. All rights reserved.

KW - Game theory

KW - Networks

KW - Allocations

KW - Robust receding horizon control

KW - NETWORKED MULTIAGENT SYSTEMS

KW - MODEL

U2 - 10.1016/j.automatica.2017.12.062

DO - 10.1016/j.automatica.2017.12.062

M3 - Article

SN - 0005-1098

VL - 90

SP - 204

EP - 211

JO - Automatica

JF - Automatica

ER -

Consensus in opinion dynamics as a repeated game

Abstract

Keywords

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