Large-scale games in large-scale systems

Research output: Contribution to conferencePaperpeer-review

Abstract

Many real-world problems modeled by stochastic games have huge state and/or action spaces, leading to the well-known curse of dimensionality. The complexity of the analysis of large-scale systems is dramatically reduced by exploiting mean field limit and dynamical system viewpoints. Under regularity assumptions and specific time-scaling techniques, the evolution of the mean field limit can be expressed in terms of deterministic or stochastic equation or inclusion (difference or differential). In this paper, we overview recent advances of large-scale games in large-scale systems. We focus in particular on population games, stochastic population games and mean field stochastic games. Considering long-term payoffs, we characterize the mean field optimality equations by using mean field dynamic programming principle and Kolmogorov forward equations.

Original languageEnglish (US)
Pages9-17
Number of pages9
DOIs
StatePublished - 2011
Event5th International ICST Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2011 - Cachan, France
Duration: May 16 2011May 20 2011

Other

Other5th International ICST Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2011
CountryFrance
CityCachan
Period5/16/115/20/11

ASJC Scopus subject areas

  • Instrumentation

Fingerprint Dive into the research topics of 'Large-scale games in large-scale systems'. Together they form a unique fingerprint.

Cite this