Risk-sensitive mean field stochastic games

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

Abstract

Recently, there has been much interest in understanding the behavior of large-scale systems in dynamic environment. The complexity of the analysis of large-scale systems is dramatically reduced by exploiting the mean field approach leading to macroscopic dynamical systems. Under regularity assumptions and specific time-scaling techniques the evolution of the mean field limit can be expressed in deterministic or stochastic equation or inclusion (difference or differential). In this paper, we study a risk-sensitive mean field stochastic game with discounted and total payoff criterion. We provide a risk-sensitive mean field system for the long-term total payoff and derive backward-forward mean field equations. In contrast to risk-neutral discounted case, we show the non-existence of stationary mean field response in a simple scenario with two actions for each generic player.

Original languageEnglish (US)
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Pages4264-4269
Number of pages6
DOIs
StatePublished - Dec 1 2011
Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
Duration: Dec 12 2011Dec 15 2011

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
CountryUnited States
CityOrlando, FL
Period12/12/1112/15/11

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

Tembine, H. (2011). Risk-sensitive mean field stochastic games. In 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 (pp. 4264-4269). [6160218] (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2011.6160218