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

G. Ajmone Marsan, N. Bellomo*, L. Gibelli

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1051-1093
Number of pages43
JournalMathematical Models and Methods in Applied Sciences
Volume26
Issue number6
Early online date31 Mar 2016
DOIs
Publication statusPublished - 15 Jun 2016

Keywords

  • active particles
  • economy
  • evolution
  • Kinetic theory
  • learning
  • social systems
  • stochastic differential games

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