Oblivious equilibrium for stochastic games with concave utility

Sachin Adlakha, Ramesh Johari, Gabriel Weintraub, Andrea Goldsmith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We study stochastic games with a large number of players, where players are coupled via their payoff functions. A standard solution concept for stochastic games is Markov perfect equilibrium (MPE). In MPE, each player's strategy is a function of its own state as well as the state of other players. This makes MPE computationally prohibitive as the number of players becomes large. An approximate solution concept called oblivious equilibrium (OE) was introduced by Weintraub et al., where each player's decision depends only on its own state and the "long-run average" state of other players. This makes OE computationally more tractable than MPE. It was shown that under a set of assumptions, as the number of players becomes large, OE closely approximates MPE. However, these assumptions require the computation of OE and verifying that the resulting stationary distribution satisfies a certain light-tail condition. In this paper, we derive exogenous conditions on the state dynamics and the payoff function under which the light-tail condition holds. A key condition is that the agents' payoffs are concave in their own state and actions. These exogenous conditions enable us to characterize a family of stochastic games in which OE is a good approximation for MPE.

Original languageEnglish (US)
Title of host publication46th Annual Allerton Conference on Communication, Control, and Computing
Pages1304-1308
Number of pages5
DOIs
StatePublished - 2008
Externally publishedYes
Event46th Annual Allerton Conference on Communication, Control, and Computing - Monticello, IL, United States
Duration: Sep 24 2008Sep 26 2008

Publication series

Name46th Annual Allerton Conference on Communication, Control, and Computing

Other

Other46th Annual Allerton Conference on Communication, Control, and Computing
CountryUnited States
CityMonticello, IL
Period9/24/089/26/08

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software
  • Control and Systems Engineering
  • Communication

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