MODELLING THE DYNAMICS OF SOCIAL PROTESTS: MEAN-FIELD GAMES AND INVERSE PROBLEMS

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In recent years, there has been an increase in social tension all over the world, which manifests itself in the form of social protests. Understanding the dynamics of street protests and studying the factors that can influence their occurrence, duration and intensity is crucial for the stable and sustainable development of society. One of the approaches to constructing various scenarios of social dynamics is to use the theory of mean-field games. A combined mathematical model of social protests based on the approach of mid-level games and dynamic systems is proposed. Numerical results of solving the inverse problem based on statistical data of the social movement in France for 2018–2019 are presented.

作者简介

A. Glukhov

Sobolev Institute of Mathematics of Siberian Branch of RAS

Email: a.glukhov@alumni.nsu.ru
Novosibirsk, Russia

M. Shishlenin

Sobolev Institute of Mathematics of Siberian Branch of RAS

Email: m.a.shishlenin@mail.ru
Novosibirsk, Russia

N. Trusov

Federal Research Center “Informatics and Control” of RAS

Email: trunick.10.96@gmail.com
Moscow, Russia

参考

  1. World Protests: a Study of Key Protest Issues in the 21st Century / I. Ortiz, S. Burke, M. Berrada, H. Cort´es. — Cham : Palgrave Macmillan Cham, 2022. — 185 p.
  2. Why do Romanians take to the streets? A spatial analysis of Romania’s 2016–2017 protests / A.S. Nicula, M.S. Stoica, E.M. Birsanuc, T.C. Man // Romanian J. Political Sci. — 2020. — V. 19, № 2. — P. 201–202.
  3. Schussman, A. Process and protest: accounting for individual protest participation / A. Schussman, S.A. Soule // Social Forces. — 2005. — V. 84, № 2. — P. 1083–1108.
  4. Jetten, J. How economic inequality fuels the rise and persistence of the yellow vest movement / J. Jetten, F. Mols, H.P. Selvanathan // Intern. Review of Social Psychology. — 2020. — V. 33, № 1. — P. 2.
  5. Dynamical modelling of street protests using the Yellow Vest Movement and Khabarovsk as case studies / A. Alsulami, A. Glukhov, M. Shishlenin, S. Petrovskii // Scientific Reports. — 2022. — V. 12, № 1. — Art. 20447.
  6. Petrovskii, S. Understanding street protests: from a mathematical model to protest management / S. Petrovskii, M. Shishlenin, A. Glukhov // PLoS ONE. — 2025. — V. 20, № 4. — Art. e0319837.
  7. A numerical algorithm for inverse problem from partial boundary measurement arising from mean field game problem / Y.T. Chow, S.W. Fung, S. Liu [et al.] // Inverse Problems. — 2023. — V. 39, № 1. — Art. 014001.
  8. Mean-field limits for entropic multi-population dynamical systems / S. Almi, C. D’Eramo, M. Morandotti, F. Solombrino // Milan J. Math. — 2023. — V. 91, № 1. — P. 175–212.
  9. Liu, H. Inverse problems for mean field games / H. Liu, C. Mou, S. Zhang // Inverse Problems. — 2023. — V. 39, № 8. — Art. 085003.
  10. Cannarsa, P. Existence and uniqueness for mean field games with state constraints / P. Cannarsa, R. Capuani // Springer INdAM Series. — 2018. — V. 28. — P. 49–71.
  11. Gu´eant, O. An existence and uniqueness result for mean field games with congestion effect on graphs / O. Gu´eant // Applied Mathematics and Optimization. — 2015. — V. 72, № 2 — P. 291–303.
  12. Klibanov, M.V. On the mean field games system with lateral Cauchy data via Carleman estimates / M.V. Klibanov, J. Li, H. Liu // J. Inverse Ill-Posed Problems. — 2024. — V. 32, № 2. — P. 277–295.
  13. Klibanov, M.V. Lipschitz stability estimate and uniqueness in the retrospective analysis for the Mean Field Games system via two Carleman estimates / M.V. Klibanov, Y. Averboukh // SIAM J. on Mathematical Analysis. — 2024. — V. 56, № 1. — P. 616–636.
  14. Berestycki, H. A model of riots dynamics: shocks, diffusion and thresholds / H. Berestycki, J-P. Nadal, N. Rod´ıguez // Networks & Heterogeneous Media. — 2015. — V. 10, № 3. — P. 443–475.
  15. Lasry, J.-M. Mean field games / J.-M. Lasry, P.-L. Lions // Japanese J. Math. — 2007. — V. 2, № 1. — P. 229–260.
  16. Huang, M. The NCE (mean field) principle with locality dependent cost interactions / M. Huang, P.E. Caines, R.P. Malham´e // IEEE Trans. Automat. Control. — 2010. — V. 55, № 12. — P. 2799– 2805.
  17. Bauso, D. Opinion dynamics and stubbornness via multipopulation mean-field games / D. Bauso, D.R. Pesenti, M. Tolotti // J. Optim. Theory Appl. — 2016. — V. 170, № 1. — P. 266–293.
  18. Kolokoltsov, V.N. Mean field game model of corruption / V.N. Kolokoltsov, O. Malafeyev // Dynamic Games and Applications. — 2017. — V. 7, № 1. — P. 34–47.
  19. Shananin, A. The household behavior modeling based on mean field games approach / A. Shananin, N. Trusov // Lobachevskii J. Math. — 2021. — V. 42, № 7. — P. 1738–1752.
  20. A trading execution model based on mean field games and optimal control / L. Fatone, F. Mariani, M.C. Recchioni, F. Zirilli // Appl. Math. — 2014. — V. 5, № 19. — P. 3091–3116.
  21. Lapin, A. Numerical solution of a parabolic optimal control problem arising in economics and management / A. Lapin, S. Zhang, S. Lapin // Appl. Math. Comput. — 2019. — V. 361. — P. 715–729.
  22. Zhang, S. Modeling and computation of mean field equilibria in producers’ game with emission permits trading / S. Zhang, X. Wang, A. Shanain // Commun. Nonlin. Sci. Numer. Simul. — 2016. — V. 37. — P. 238–248.
  23. Trusov, N.V. Numerical study of the stock market crises based on mean field games approach / N.V. Trusov // J. Inverse Ill-Posed Problems. — 2021. — V. 29, № 6. — P. 849–865.
  24. Lachapelle, A. Computation of mean field equilibria in economics / A. Lachapelle, J. Salomon, G. Turinici / Mathematical Models and Methods in Applied Sciences. — 2010. — V. 20, № 04. — P. 567–588.
  25. Bensoussan, A. Mean Field Games and Mean Field Type Control Theory / A. Bensoussan, J. Frehse, P. Yam. — New York : Springer, 2013. — 128 p.
  26. Kabanikhin, S.I. Quasi-solution in inverse coefficient problems / S.I. Kabanikhin, M.A. Shishlenin // J. Inverse Ill-Posed Problems. — 2008. — V. 16, № 7. — P. 705–713.

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