On Controlling a Coevolutionary Model of Actions and Opinions
(2024) 63rd IEEE Conference on Decision and Control, CDC 2024 p.4550-4555- Abstract
We deal with a control problem for a complex social network in which each agent has an action and an opinion, evolving according to a coevolutionary model. In particular, we consider a scenario in which a committed minority - a set of stubborn nodes - aims to steer a population, initially at a consensus, to a different consensus state. Our study focuses on determining the conditions under which such a goal is reached, and ultimately, how to optimally define a minimal committed minority. First, we derive a general monotone convergence result for the controlled coevolutionary model, under mild and general assumptions on the agents' revision sequence. Then, we build on our theoretical result to propose a systematic approach to investigate... (More)
We deal with a control problem for a complex social network in which each agent has an action and an opinion, evolving according to a coevolutionary model. In particular, we consider a scenario in which a committed minority - a set of stubborn nodes - aims to steer a population, initially at a consensus, to a different consensus state. Our study focuses on determining the conditions under which such a goal is reached, and ultimately, how to optimally define a minimal committed minority. First, we derive a general monotone convergence result for the controlled coevolutionary model, under mild and general assumptions on the agents' revision sequence. Then, we build on our theoretical result to propose a systematic approach to investigate the research problem.
(Less)
- author
- Raineri, Roberta ; Como, Giacomo LU ; Fagnani, Fabio ; Ye, Mengbin and Zino, Lorenzo
- organization
- publishing date
- 2024
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2024 IEEE 63rd Conference on Decision and Control, CDC 2024
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 63rd IEEE Conference on Decision and Control, CDC 2024
- conference location
- Milan, Italy
- conference dates
- 2024-12-16 - 2024-12-19
- external identifiers
-
- scopus:86000542238
- ISBN
- 9798350316339
- DOI
- 10.1109/CDC56724.2024.10886195
- language
- English
- LU publication?
- yes
- id
- 82bebcd9-acdd-4e1b-8950-5c9d87485bd0
- date added to LUP
- 2025-06-04 09:24:00
- date last changed
- 2025-06-04 09:41:32
@inproceedings{82bebcd9-acdd-4e1b-8950-5c9d87485bd0,
abstract = {{<p>We deal with a control problem for a complex social network in which each agent has an action and an opinion, evolving according to a coevolutionary model. In particular, we consider a scenario in which a committed minority - a set of stubborn nodes - aims to steer a population, initially at a consensus, to a different consensus state. Our study focuses on determining the conditions under which such a goal is reached, and ultimately, how to optimally define a minimal committed minority. First, we derive a general monotone convergence result for the controlled coevolutionary model, under mild and general assumptions on the agents' revision sequence. Then, we build on our theoretical result to propose a systematic approach to investigate the research problem.</p>}},
author = {{Raineri, Roberta and Como, Giacomo and Fagnani, Fabio and Ye, Mengbin and Zino, Lorenzo}},
booktitle = {{2024 IEEE 63rd Conference on Decision and Control, CDC 2024}},
isbn = {{9798350316339}},
language = {{eng}},
pages = {{4550--4555}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{On Controlling a Coevolutionary Model of Actions and Opinions}},
url = {{http://dx.doi.org/10.1109/CDC56724.2024.10886195}},
doi = {{10.1109/CDC56724.2024.10886195}},
year = {{2024}},
}