Opinion dynamics, stubbornness and mean-field games

Proceedings of the IEEE Conference on Decision and Control

Volumn 2015-February, Issue February, 2014, Pages 3475-3480

  Bauso, Dario ^a   Pesenti, Raffaele ^b  

^a UNIVERSITY OF PALERMO   (Italy)

^b CA' FOSCARI UNIVERSITY OF VENICE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

GAME THEORY;

CONTROL POLICY; MEAN FIELD GAMES; OPINION DYNAMICS; OVER THE HORIZONS;

FOKKER PLANCK EQUATION;

EID: 84988243985     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2014.7039928     Document Type: Conference Paper

References (19)

1. D. Acemoglu and A. Ozdaglar, Opinion dynamics and learning in social networks, International Review of Economics, Vol. 1(1), pp. 3-49, 2011.
2. D. Acemoglu, G. Como, F. Fagnani, and A. Ozdaglar. "Opinion fluctuations and disagreement in social networks", Math. of Operation Research, Vol. 38(1), pp. 1-27, 2013.
3. M. Bardi, Explicit solutions of some Linear-Quadratic Mean Field Games, Network and Heterogeneous Media, 7, pp. 243-261, 2012.
4. D. Bauso, H. Tembine, and T. Başar, Robust Mean Field Games with Application to Production of an Exhaustible Resource, Proc. of 7th IFAC Symposium on Robust Control Design, Aalborg, D, 2012.
5. C. Castellano, S. Fortunato, V. Loreto, Statistical physics of social dynamics, Reviews of Modern Physics, Vol. 81, pp. 591-646, 2009.
6. G. Como and F. Fagnani, Scaling limits for continuous opinion dynamics systems, The Annals of Applied Probability, Vol. 21(4), pp. 1537-1567, 2011.
7. D.A. Gomes, J. Saude, Mean Field Games Models - A Brief Survey, Dynamic Games and Applications, Vol. 4(2), pp. 110-154, 2014.
8. O. Gueant, J.M. Lasry, and PL Lions, Mean field games and applications, Paris-Princeton Lectures, Springer, pp. 1-66, 2010.
9. M.Y. Huang, P.E. Caines, and R.P Malhamé, Individual and mass behaviour in large population stochastic wireless power control problems: centralized and Nash equilibrium solutions, Proc. IEEE Conf. on Decision and Control, HI, USA, pp. 98-103, 2003.
10. M.Y. Huang, P.E. Caines, and R.P. Malhamé, Large Population Stochastic Dynamic Games: Closed Loop Kean-Vlasov Systems and the Nash Certainty Equivalence Principle, Communications in Information and Systems, Vol. 6, no. 3, pp. 221-252, 2006.
11. M.Y. Huang, P.E. Caines, and R.P. Malhamé, Large population cost-coupled LQG problems with non-uniform agents: individual-mass behaviour and decentralized ε-Nash equilibria, IEEE Trans. on Automatic Control, Vol. 52. no. 9, pp. 1560-1571, 2007.
12. U. Krause, A discrete nonlinear and non-autonomous model of consensus formation, Communications in Difference Equations, pp. 227-236, S. Elaydi, G. Ladas, J. Popenda, and J. Rakowski editors, Gordon and Breach, Amsterdam, NL, 2000.
13. A. Lachapelle, J. Salomon, and G. Turinici, Computation of Mean Field Equilibria in Economics, Mathematical Models and Methods in Applied Sciences, Vol. 20, pp. 1-22, 2010.
14. J.M. Lasry and PL. Lions, Mean field games, Japanese Journal of Mathematics, Vol. 2, pp. 229-260, 2007.
15. K.A. Loparo and X. Feng, Stability of stochastic systems. The Control Handbook, CRC Press, pp. 1105-1126, 1996.
16. R. Pesenti, and D. Bauso, Mean Field Linear Quadratic Games with Set Up Costs, Dynamic Games and Applications, Vol. 3(1), pp. 89-104, 2013
17. A.-S. Sznitman, Topics in propagation of chaos, Springer Lecture Notes in Mathematics, Vol. 1464, pp. 165-251, 1991.
18. H. Tembine, Q. Zhu, and T. Başar, Risk-sensitive mean-field stochastic differential games, Proc. of 2011 IFAC World Congress, Milan, I, 2011.
19. H. Tembine, J.Y Le Boudec, R. El Azouzi, E. Altman, Mean field asymptotic of Markov decision evolutionary games, IEEE Gamenets 2009.