A Lyapunov Approach to Stochastic Interaction Dynamics Over Large-Scale Networks
(2024) 2024 American Control Conference, ACC 2024 In Proceedings of the American Control Conference p.4416-4421- Abstract
We study stochastic interaction network models whereby a finite population of agents, identified with the nodes of a graph, update their states in response to pairwise interactions with their neighbors as well as spontaneous mutations. These include the main epidemic models, such as the Susceptible-Infected -Susceptible, the Susceptible-Infected-Recovered, and the Susceptible-Infected-Recovered-Susceptible models. We analyze the asymptotic behavior of such systems on Erdös-Rényi random graphs, in the limit as the population size grows large. Our approach is based on the use of (approximate) Lyapunov functions for Markov chains through which we can obtain stability results in terms of the corresponding invariant probabilities and on... (More)
We study stochastic interaction network models whereby a finite population of agents, identified with the nodes of a graph, update their states in response to pairwise interactions with their neighbors as well as spontaneous mutations. These include the main epidemic models, such as the Susceptible-Infected -Susceptible, the Susceptible-Infected-Recovered, and the Susceptible-Infected-Recovered-Susceptible models. We analyze the asymptotic behavior of such systems on Erdös-Rényi random graphs, in the limit as the population size grows large. Our approach is based on the use of (approximate) Lyapunov functions for Markov chains through which we can obtain stability results in terms of the corresponding invariant probabilities and on specific concentration results for Erdos-Renyi random graphs.
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- author
- Como, Giacomo LU ; Fagnani, Fabio and Zampieri, Sandro
- organization
- publishing date
- 2024
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2024 American Control Conference, ACC 2024
- series title
- Proceedings of the American Control Conference
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2024 American Control Conference, ACC 2024
- conference location
- Toronto, Canada
- conference dates
- 2024-07-10 - 2024-07-12
- external identifiers
-
- scopus:85204464118
- ISSN
- 0743-1619
- ISBN
- 9798350382655
- DOI
- 10.23919/ACC60939.2024.10644819
- language
- English
- LU publication?
- yes
- id
- f098fbc2-f154-464d-a152-b7f27328123e
- date added to LUP
- 2024-12-02 13:05:07
- date last changed
- 2025-04-04 14:42:49
@inproceedings{f098fbc2-f154-464d-a152-b7f27328123e,
abstract = {{<p>We study stochastic interaction network models whereby a finite population of agents, identified with the nodes of a graph, update their states in response to pairwise interactions with their neighbors as well as spontaneous mutations. These include the main epidemic models, such as the Susceptible-Infected -Susceptible, the Susceptible-Infected-Recovered, and the Susceptible-Infected-Recovered-Susceptible models. We analyze the asymptotic behavior of such systems on Erdös-Rényi random graphs, in the limit as the population size grows large. Our approach is based on the use of (approximate) Lyapunov functions for Markov chains through which we can obtain stability results in terms of the corresponding invariant probabilities and on specific concentration results for Erdos-Renyi random graphs.</p>}},
author = {{Como, Giacomo and Fagnani, Fabio and Zampieri, Sandro}},
booktitle = {{2024 American Control Conference, ACC 2024}},
isbn = {{9798350382655}},
issn = {{0743-1619}},
language = {{eng}},
pages = {{4416--4421}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{Proceedings of the American Control Conference}},
title = {{A Lyapunov Approach to Stochastic Interaction Dynamics Over Large-Scale Networks}},
url = {{http://dx.doi.org/10.23919/ACC60939.2024.10644819}},
doi = {{10.23919/ACC60939.2024.10644819}},
year = {{2024}},
}