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Optimal selection of the most informative nodes for a noisy DeGroot model with stubborn agents

Raineri, Roberta ; Como, Giacomo LU and Fagnani, Fabio (2025) 2025 European Control Conference, ECC 2025 p.558-563
Abstract

Finding the optimal subset of individuals to observe in order to obtain the best estimate of the average opinion of a society is a crucial problem in a wide range of applications, including policy-making, strategic business decisions, and the analysis of sociological trends. We consider the opinion vector X to be updated according to a DeGroot opinion dynamical model with stubborn agents, subject to perturbations from external random noise, which can be interpreted as transmission errors. The objective function of the optimization problem is the variance reduction achieved by observing the equilibrium opinions of a subset KV of agents. We demonstrate that, under this specific setting, the objective function exhibits the property of... (More)

Finding the optimal subset of individuals to observe in order to obtain the best estimate of the average opinion of a society is a crucial problem in a wide range of applications, including policy-making, strategic business decisions, and the analysis of sociological trends. We consider the opinion vector X to be updated according to a DeGroot opinion dynamical model with stubborn agents, subject to perturbations from external random noise, which can be interpreted as transmission errors. The objective function of the optimization problem is the variance reduction achieved by observing the equilibrium opinions of a subset KV of agents. We demonstrate that, under this specific setting, the objective function exhibits the property of submodularity. This allows us to effectively design a Greedy Algorithm to solve the problem, significantly reducing its computational complexity. Simple examples are provided to validate our results.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2025 European Control Conference, ECC 2025
edition
2025
pages
6 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2025 European Control Conference, ECC 2025
conference location
Thessaloniki, Greece
conference dates
2025-06-24 - 2025-06-27
external identifiers
  • scopus:105030950091
ISBN
9783907144121
DOI
10.23919/ECC65951.2025.11187098
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2025 EUCA.
id
07cee4e5-757f-45f4-8e33-64252fff9a23
date added to LUP
2026-04-21 16:35:58
date last changed
2026-04-21 16:36:59
@inproceedings{07cee4e5-757f-45f4-8e33-64252fff9a23,
  abstract     = {{<p>Finding the optimal subset of individuals to observe in order to obtain the best estimate of the average opinion of a society is a crucial problem in a wide range of applications, including policy-making, strategic business decisions, and the analysis of sociological trends. We consider the opinion vector X to be updated according to a DeGroot opinion dynamical model with stubborn agents, subject to perturbations from external random noise, which can be interpreted as transmission errors. The objective function of the optimization problem is the variance reduction achieved by observing the equilibrium opinions of a subset KV of agents. We demonstrate that, under this specific setting, the objective function exhibits the property of submodularity. This allows us to effectively design a Greedy Algorithm to solve the problem, significantly reducing its computational complexity. Simple examples are provided to validate our results.</p>}},
  author       = {{Raineri, Roberta and Como, Giacomo and Fagnani, Fabio}},
  booktitle    = {{2025 European Control Conference, ECC 2025}},
  isbn         = {{9783907144121}},
  language     = {{eng}},
  pages        = {{558--563}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Optimal selection of the most informative nodes for a noisy DeGroot model with stubborn agents}},
  url          = {{http://dx.doi.org/10.23919/ECC65951.2025.11187098}},
  doi          = {{10.23919/ECC65951.2025.11187098}},
  year         = {{2025}},
}