Meanfield games and model predictive control

Pierre Degond Imperial College London Michael Herty RWTH Aachen University, Department of Mathematics Jian-Guo Liu Duke University

Optimization and Control mathscidoc:1702.27003

Distinguished Paper Award in 2018

Mean-Field Games are games with a continuum of players that incorporate the time-dimension through a control-theoretic approach. Recently, simpler approaches relying on the Best Reply Strategy have been proposed. They assume that the agents navigate their strategies towards their goal by taking the direction of steepest descent of their cost function (i.e. the opposite of the utility function). In this paper, we explore the link between Mean-Field Games and the Best Reply Strategy approach. This is done by introducing a Model Predictive Control framework, which consists of setting the Mean-Field Game over a short time interval which recedes as time moves on. We show that the Model Predictive Control offers a compromise between a possibly unrealistic Mean-Field Game approach and the sub-optimal Best Reply Strategy.
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  title={Meanfield games and model predictive control},
  author={Pierre Degond, Michael Herty, and Jian-Guo Liu},
Pierre Degond, Michael Herty, and Jian-Guo Liu. Meanfield games and model predictive control. 2017.
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