Master adjoint systems in mean-field-type games

2021 ◽  
Vol 21 (4) ◽  
pp. 623-650
Author(s):  
Hamidou Tembine
Keyword(s):  
Mean Field ◽  
Field Type ◽  
Adjoint Systems

scholarly journals COVID-19: A Data-Driven Mean-Field-Type Game Perspective

2020 ◽  
Author(s):  
Hamidou Tembine
Keyword(s):  
Mean Field ◽  
Decision Makers ◽  
Data Driven ◽  
Feedback Form ◽  
State Spaces ◽  
Hospital Capacity ◽  
Field Type ◽  
Adjoint Systems ◽  
Continuous State ◽  
Reported Data

In this article, a class of mean-field-type games with discrete-continuous state spaces is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive unnormalized master adjoint systems (MASS). The methodology is shown to be flexible enough to capture multi-class interaction in epidemic propagation in which multiple authorities are risk-aware atomic decision-makers and individuals are risk-aware non-atomic decision-makers. Based on MASS, we present a data-driven modelling and analytics for mitigating Coronavirus Disease 2019 (COVID-19). The model integrates untested cases, age-structure, decision-making, gender, pre-existing health conditions, location, testing capacity, hospital capacity, mobility map on local areas, in-city, inter-cities, and international. It shown that the data-driven model can capture most of the reported data on COVID-19 on confirmed cases, deaths, recovered, number of testing and number of active cases in 66+ countries. The model also reports non-Gaussianity and non-exponential properties in 15+ countries.

scholarly journals COVID-19: Data-Driven Mean-Field-Type Game Perspective

Games ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 51
Author(s):  
Hamidou Tembine
Keyword(s):  
Mean Field ◽  
Decision Makers ◽  
Data Driven ◽  
Feedback Form ◽  
State Spaces ◽  
Field Type ◽  
Adjoint Systems ◽  
Continuous State ◽  
Non Gaussian ◽  
Reported Data

In this article, a class of mean-field-type games with discrete-continuous state spaces is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive unnormalized master adjoint systems (MASS). The methodology is shown to be flexible enough to capture multi-class interaction in epidemic propagation in which multiple authorities are risk-aware atomic decision-makers and individuals are risk-aware non-atomic decision-makers. Based on MASS, we present a data-driven modelling and analytics for mitigating Coronavirus Disease 2019 (COVID-19). The model integrates untested cases, age-structure, decision-making, gender, pre-existing health conditions, location, testing capacity, hospital capacity, and a mobility map of local areas, including in-cities, inter-cities, and internationally. It is shown that the data-driven model can capture most of the reported data on COVID-19 on confirmed cases, deaths, recovered, number of testing and number of active cases in 66+ countries. The model also reports non-Gaussian and non-exponential properties in 15+ countries.

Mean-field type forward-backward doubly stochastic differential equations and related stochastic differential games

2020 ◽  
Vol 15 (6) ◽  
pp. 1307-1326
Author(s):  
Qingfeng Zhu ◽  
Lijiao Su ◽  
Fuguo Liu ◽  
Yufeng Shi ◽  
Yong’ao Shen ◽  
...  
Keyword(s):  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Differential Games ◽  
Mean Field ◽  
Stochastic Differential Games ◽  
Field Type ◽  
Doubly Stochastic

Mean-Field-Type Games for Engineers

2021 ◽  
Author(s):  
Julian Barreiro-Gomez ◽  
Hamidou Tembine
Keyword(s):  
Mean Field ◽  
Field Type

Coexistence of cluster structure and mean-field-type structure in medium-weight nuclei

2007 ◽  
Vol 787 (1-4) ◽  
pp. 547-552
Author(s):  
Y. Taniguchi ◽  
M. Kimura ◽  
Y. Kanada-En'yo ◽  
H. Horiuchi
Keyword(s):  
Cluster Structure ◽  
Mean Field ◽  
Type Structure ◽  
Field Type ◽  
Medium Weight
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