scholarly journals Probabilistic Approach to Finite State Mean Field Games

2018 ◽  
Vol 81 (2) ◽  
pp. 253-300 ◽  
Author(s):  
Alekos Cecchin ◽  
Markus Fischer
Author(s):  
René Carmona ◽  
Peiqi Wang

We develop a probabilistic approach to continuous-time finite state mean field games. Based on an alternative description of continuous-time Markov chains by means of semimartingales and the weak formulation of stochastic optimal control, our approach not only allows us to tackle the mean field of states and the mean field of control at the same time, but also extends the strategy set of players from Markov strategies to closed-loop strategies. We show the existence and uniqueness of Nash equilibrium for the mean field game as well as how the equilibrium of a mean field game consists of an approximative Nash equilibrium for the game with a finite number of players under different assumptions of structure and regularity on the cost functions and transition rate between states.


2016 ◽  
Vol 26 (3) ◽  
pp. 1535-1580 ◽  
Author(s):  
René Carmona ◽  
Xiuneng Zhu

Author(s):  
Diogo Gomes ◽  
Roberto M. Velho ◽  
Marie-Therese Wolfram

In this paper, we present different applications of finite state mean field games to socio-economic sciences. Examples include paradigm shifts in the scientific community or consumer choice behaviour in the free market. The corresponding finite state mean field game models are hyperbolic systems of partial differential equations, for which we present and validate different numerical methods. We illustrate the behaviour of solutions with various numerical experiments, which show interesting phenomena such as shock formation. Hence, we conclude with an investigation of the shock structure in the case of two-state problems.


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