Stochastic evolutionary differential games toward a systems theory of behavioral social dynamics

被引:108
作者
Ajmone Marsan, G. [1 ]
Bellomo, N. [2 ,3 ]
Gibelli, L. [4 ]
机构
[1] Org Econ Cooperat & Dev, Paris, France
[2] King Abdulaziz Univ, Fac Sci, Dept Math, Jeddah, Saudi Arabia
[3] Politecn Torino, Turin, Italy
[4] Politecn Torino, Dept Math Sci, Turin, Italy
关键词
Kinetic theory; active particles; stochastic differential games; evolution; learning; social systems; economy; MEAN-FIELD GAMES; MODELING COMPLEX-SYSTEMS; OPINION FORMATION; MATHEMATICAL-THEORY; BOLTZMANN-EQUATION; KINETIC-EQUATIONS; ACTIVE PARTICLES; MAJORITY-RULE; COMPETITION; NETWORKS;
D O I
10.1142/S0218202516500251
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper proposes a systems approach to social sciences based on a mathematical framework derived from a generalization of the mathematical kinetic theory and of theoretical tools of game theory. Social systems are modeled as a living evolutionary ensemble composed of many individuals, who express specific strategies, cooperate, compete and might aggregate into groups which pursue a common interest. A critical analysis on the complexity features of social system is developed and a differential structure is derived to provide a general framework toward modeling. Then, a case study shows how the systems approach is applied. Moreover, it is shown how the theory leads to the interpretation and use of the so-called big data. Finally some research perspectives are brought to the attention of readers.
引用
收藏
页码:1051 / 1093
页数:43
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