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Accelerating opponent strategy inference for voting dynamics on complex networks

Accelerating opponent strategy inference for voting dynamics on complex networks
Accelerating opponent strategy inference for voting dynamics on complex networks
In this paper, we study the problem of opponent strategy inference from observations of information diffusion in voting dynamics on complex networks. We demonstrate that, by deploying resources of an active controller, it is possible to influence the information dynamics in such a way that opponent strategies can be more easily uncovered. To this end, we use the framework of maximum likelihood estimation and the Fisher information to construct confidence intervals for opponent strategy estimates. We then design heuristics for optimally deploying resources with the aim of minimizing the variance of estimates. In the first part of the paper, we focus on inferring an opponent strategy at a single node. Here, we derive optimal resource allocations, finding that, for low controller budget, resources should be focused on the inferred node and, for large budget, on the inferred nodes' neighbours.
In the second part, we extend the setting to inferring opponent strategies over the entire network. We find that opponents are the harder to detect the more heterogeneous networks are, even with optimal targeting.
Complex networks, Network control, Network inference, Voting dynamics
1860-949X
844-856
Springer Science and Business Media Deutschland GmbH
Cai, Zhongqi
b3ce4c1b-e545-4a86-9592-960542756e14
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7
Benito, Rosa Maria
Cherifi, Chantal
Cherifi, Hocine
Moro, Esteban
Rocha, Luis M.
Sales-Pardo, Marta
Cai, Zhongqi
b3ce4c1b-e545-4a86-9592-960542756e14
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7
Benito, Rosa Maria
Cherifi, Chantal
Cherifi, Hocine
Moro, Esteban
Rocha, Luis M.
Sales-Pardo, Marta

Cai, Zhongqi, Gerding, Enrico and Brede, Markus (2022) Accelerating opponent strategy inference for voting dynamics on complex networks. Benito, Rosa Maria, Cherifi, Chantal, Cherifi, Hocine, Moro, Esteban, Rocha, Luis M. and Sales-Pardo, Marta (eds.) In Complex Networks and Their Applications X - Proceedings of the 10th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021. vol. 1015, Springer Science and Business Media Deutschland GmbH. pp. 844-856 . (doi:10.1007/978-3-030-93409-5_69).

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, we study the problem of opponent strategy inference from observations of information diffusion in voting dynamics on complex networks. We demonstrate that, by deploying resources of an active controller, it is possible to influence the information dynamics in such a way that opponent strategies can be more easily uncovered. To this end, we use the framework of maximum likelihood estimation and the Fisher information to construct confidence intervals for opponent strategy estimates. We then design heuristics for optimally deploying resources with the aim of minimizing the variance of estimates. In the first part of the paper, we focus on inferring an opponent strategy at a single node. Here, we derive optimal resource allocations, finding that, for low controller budget, resources should be focused on the inferred node and, for large budget, on the inferred nodes' neighbours.
In the second part, we extend the setting to inferring opponent strategies over the entire network. We find that opponents are the harder to detect the more heterogeneous networks are, even with optimal targeting.

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Accepted/In Press date: 29 September 2021
Published date: 1 January 2022
Additional Information: Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2022 Elsevier B.V., All rights reserved.
Venue - Dates: 10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021, , Madrid, Spain, 2021-11-30 - 2021-12-02
Keywords: Complex networks, Network control, Network inference, Voting dynamics

Identifiers

Local EPrints ID: 451891
URI: http://eprints.soton.ac.uk/id/eprint/451891
ISSN: 1860-949X
PURE UUID: 803c3e9f-c7d9-42a0-b6f7-aeee556602cc
ORCID for Enrico Gerding: ORCID iD orcid.org/0000-0001-7200-552X

Catalogue record

Date deposited: 02 Nov 2021 17:44
Last modified: 05 May 2022 01:39

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Contributors

Author: Zhongqi Cai
Author: Enrico Gerding ORCID iD
Author: Markus Brede
Editor: Rosa Maria Benito
Editor: Chantal Cherifi
Editor: Hocine Cherifi
Editor: Esteban Moro
Editor: Luis M. Rocha
Editor: Marta Sales-Pardo

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