Title :
On oblivious equilibrium in large population stochastic games
Author :
Adlakha, Sachin ; Johari, Ramesh ; Weintraub, Gabriel Y. ; Goldsmith, Andrea
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Abstract :
We study stochastic games with a large number of players, where players are coupled via their payoff functions. A standard solution concept for such games is Markov perfect equilibrium (MPE). It is well known that the computation of MPE suffers from the “curse of dimensionality.” To deal with this complexity, several researchers have introduced the idea of oblivious equilibrium (OE). In OE, each player reacts to only the long-run average state of other players. In this paper, we study existence of OE, and also find conditions under which OE approximates MPE well.
Keywords :
Markov processes; stochastic games; Markov perfect equilibrium; oblivious equilibrium; payoff function; stochastic games; Approximation methods; Convergence; Equations; Games; Kernel; Markov processes;
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.2010.5717048