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Large-scale games in large-scale systems

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 note, 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 systems using Bellman and Kolmogorov forward equations.
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Contributor : Catherine Magnet <>
Submitted on : Friday, December 16, 2011 - 2:44:03 PM
Last modification on : Thursday, March 29, 2018 - 11:06:05 AM


  • HAL Id : hal-00652861, version 1



Hamidou Tembine. Large-scale games in large-scale systems. 5th International ICST Conference on Performance Evaluation Methodologies and Tools, May 2011, Cachan, France. pp.1-8. ⟨hal-00652861⟩



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