Title :
Mean field equilibrium in dynamic games with complementarities
Author :
Adlakha, Sachin ; Johari, Ramesh
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Abstract :
We study stochastic dynamic games with a large number of players, where players are coupled via their payoff functions. We consider mean field equilibrium for such games: in such an equilibrium, each player reacts to only the long run average state of other players. In this paper we focus on a special class of stochastic games, where a player experiences strategic complementarities from other players; formally the payoff of a player has increasing differences between her own state and the aggregate empirical distribution of the states of other players. We find necessary conditions for the existence of a mean field equilibrium in such games. Furthermore, we show that there exist a “largest” and “smallest” equilibrium among all those where the equilibrium strategy used by a player is nondecreasing.
Keywords :
stochastic games; complementarities; mean field equilibrium; payoff functions; stochastic dynamic games; Convex functions; Games; Kernel; Lattices; Markov processes; Upper bound;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5717416