Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes

Competition and collaboration are at the heart of multiagent probabilistic spreading processes. The battle for public opinion and competitive marketing campaigns are typical examples of the former, while the joint spread of multiple diseases such as HIV and tuberculosis demonstrates the latter. Thes...

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Autores principales:	Hanlin Sun, David Saad, Andrey Y. Lokhov
Formato:	article
Lenguaje:	EN
Publicado:	American Physical Society 2021
Materias:	Physics QC1-999
Acceso en línea:	https://doaj.org/article/0291d3814f2f4c7c90f849ed52a2e83e
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spelling	oai:doaj.org-article:0291d3814f2f4c7c90f849ed52a2e83e2021-12-02T17:56:26ZCompetition, Collaboration, and Optimization in Multiple Interacting Spreading Processes10.1103/PhysRevX.11.0110482160-3308https://doaj.org/article/0291d3814f2f4c7c90f849ed52a2e83e2021-03-01T00:00:00Zhttp://doi.org/10.1103/PhysRevX.11.011048http://doi.org/10.1103/PhysRevX.11.011048https://doaj.org/toc/2160-3308Competition and collaboration are at the heart of multiagent probabilistic spreading processes. The battle for public opinion and competitive marketing campaigns are typical examples of the former, while the joint spread of multiple diseases such as HIV and tuberculosis demonstrates the latter. These spreads are influenced by the underlying network topology, the infection rates between network constituents, recovery rates, and, equally important, the interactions between the spreading processes themselves. Here, for the first time, we derive dynamic message-passing equations that provide an exact description of the dynamics of two, interacting, unidirectional spreading processes on tree graphs, and we develop systematic low-complexity models that predict the spread on general graphs. We also develop a theoretical framework for the optimal control of interacting spreading processes through optimized resource allocation under budget constraints and within a finite time window. Derived algorithms can be used to maximize the desired spread in the presence of a rival competitive process and to limit the spread through vaccination in the case of coupled infectious diseases. We demonstrate the efficacy of the framework and optimization method on both synthetic and real-world networks.Hanlin SunDavid SaadAndrey Y. LokhovAmerican Physical SocietyarticlePhysicsQC1-999ENPhysical Review X, Vol 11, Iss 1, p 011048 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physics QC1-999
spellingShingle	Physics QC1-999 Hanlin Sun David Saad Andrey Y. Lokhov Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
description	Competition and collaboration are at the heart of multiagent probabilistic spreading processes. The battle for public opinion and competitive marketing campaigns are typical examples of the former, while the joint spread of multiple diseases such as HIV and tuberculosis demonstrates the latter. These spreads are influenced by the underlying network topology, the infection rates between network constituents, recovery rates, and, equally important, the interactions between the spreading processes themselves. Here, for the first time, we derive dynamic message-passing equations that provide an exact description of the dynamics of two, interacting, unidirectional spreading processes on tree graphs, and we develop systematic low-complexity models that predict the spread on general graphs. We also develop a theoretical framework for the optimal control of interacting spreading processes through optimized resource allocation under budget constraints and within a finite time window. Derived algorithms can be used to maximize the desired spread in the presence of a rival competitive process and to limit the spread through vaccination in the case of coupled infectious diseases. We demonstrate the efficacy of the framework and optimization method on both synthetic and real-world networks.
format	article
author	Hanlin Sun David Saad Andrey Y. Lokhov
author_facet	Hanlin Sun David Saad Andrey Y. Lokhov
author_sort	Hanlin Sun
title	Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
title_short	Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
title_full	Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
title_fullStr	Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
title_full_unstemmed	Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
title_sort	competition, collaboration, and optimization in multiple interacting spreading processes
publisher	American Physical Society
publishDate	2021
url	https://doaj.org/article/0291d3814f2f4c7c90f849ed52a2e83e
work_keys_str_mv	AT hanlinsun competitioncollaborationandoptimizationinmultipleinteractingspreadingprocesses AT davidsaad competitioncollaborationandoptimizationinmultipleinteractingspreadingprocesses AT andreyylokhov competitioncollaborationandoptimizationinmultipleinteractingspreadingprocesses
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Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes

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