Heuristic assessment of choices for risk network control

Abstract Data-driven risk networks describe many complex system dynamics arising in fields such as epidemiology and ecology. They lack explicit dynamics and have multiple sources of cost, both of which are beyond the current scope of traditional control theory. We construct the global economy risk n...

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Autores principales:	Christopher Brissette, Xiang Niu, Chunheng Jiang, Jianxi Gao, Gyorgy Korniss, Boleslaw K. Szymanski
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/51ff6046cd754aaf8947b0210ebc295f
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spelling	oai:doaj.org-article:51ff6046cd754aaf8947b0210ebc295f2021-12-02T14:37:21ZHeuristic assessment of choices for risk network control10.1038/s41598-021-85432-x2045-2322https://doaj.org/article/51ff6046cd754aaf8947b0210ebc295f2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85432-xhttps://doaj.org/toc/2045-2322Abstract Data-driven risk networks describe many complex system dynamics arising in fields such as epidemiology and ecology. They lack explicit dynamics and have multiple sources of cost, both of which are beyond the current scope of traditional control theory. We construct the global economy risk network by combining the consensus of experts from the World Economic Forum with risk activation data to define its topology and interactions. Many of these risks, including extreme weather and drastic inflation, pose significant economic costs when active. We introduce a method for converting network interaction data into continuous dynamics to which we apply optimal control. We contribute the first method for constructing and controlling risk network dynamics based on empirically collected data. We simulate applying this method to control the spread of COVID-19 and show that the choice of risks through which the network is controlled has significant influence on both the cost of control and the total cost of keeping network stable. We additionally describe a heuristic for choosing the risks trough which the network is controlled, given a general risk network.Christopher BrissetteXiang NiuChunheng JiangJianxi GaoGyorgy KornissBoleslaw K. SzymanskiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Christopher Brissette Xiang Niu Chunheng Jiang Jianxi Gao Gyorgy Korniss Boleslaw K. Szymanski Heuristic assessment of choices for risk network control
description	Abstract Data-driven risk networks describe many complex system dynamics arising in fields such as epidemiology and ecology. They lack explicit dynamics and have multiple sources of cost, both of which are beyond the current scope of traditional control theory. We construct the global economy risk network by combining the consensus of experts from the World Economic Forum with risk activation data to define its topology and interactions. Many of these risks, including extreme weather and drastic inflation, pose significant economic costs when active. We introduce a method for converting network interaction data into continuous dynamics to which we apply optimal control. We contribute the first method for constructing and controlling risk network dynamics based on empirically collected data. We simulate applying this method to control the spread of COVID-19 and show that the choice of risks through which the network is controlled has significant influence on both the cost of control and the total cost of keeping network stable. We additionally describe a heuristic for choosing the risks trough which the network is controlled, given a general risk network.
format	article
author	Christopher Brissette Xiang Niu Chunheng Jiang Jianxi Gao Gyorgy Korniss Boleslaw K. Szymanski
author_facet	Christopher Brissette Xiang Niu Chunheng Jiang Jianxi Gao Gyorgy Korniss Boleslaw K. Szymanski
author_sort	Christopher Brissette
title	Heuristic assessment of choices for risk network control
title_short	Heuristic assessment of choices for risk network control
title_full	Heuristic assessment of choices for risk network control
title_fullStr	Heuristic assessment of choices for risk network control
title_full_unstemmed	Heuristic assessment of choices for risk network control
title_sort	heuristic assessment of choices for risk network control
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/51ff6046cd754aaf8947b0210ebc295f
work_keys_str_mv	AT christopherbrissette heuristicassessmentofchoicesforrisknetworkcontrol AT xiangniu heuristicassessmentofchoicesforrisknetworkcontrol AT chunhengjiang heuristicassessmentofchoicesforrisknetworkcontrol AT jianxigao heuristicassessmentofchoicesforrisknetworkcontrol AT gyorgykorniss heuristicassessmentofchoicesforrisknetworkcontrol AT boleslawkszymanski heuristicassessmentofchoicesforrisknetworkcontrol
_version_	1718391005077569536

Heuristic assessment of choices for risk network control

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