ON THE CONVERGENCE OF CLOSED-LOOP NASH EQUILIBRIA TO THE MEAN FIELD GAME LIMIT

被引:54
|
作者
Lacker, Daniel [1 ]
机构
[1] Columbia Univ, Dept Ind Engn & Operat Res, New York, NY 10027 USA
来源
ANNALS OF APPLIED PROBABILITY | 2020年 / 30卷 / 04期
关键词
Mean field games; stochastic differential games; closed-loop controls; McKean-Vlasov equations; relaxed controls; STOCHASTIC DIFFERENTIAL-GAMES; VLASOV SYSTEMS; PROPAGATION; EXISTENCE; MIMICKING; EQUATIONS; CHAOS; STATE;
D O I
10.1214/19-AAP1541
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper continues the study of the mean field game (MFG) conver- gence problem: In what sense do the Nash equilibria of n-player stochastic differential games converge to the mean field game as n -> infinity? Previous work on this problem took two forms. First, when the n-player equilibria are openloop, compactness arguments permit a characterization of all limit points of n-player equilibria as weak MFG equilibria, which contain additional randomness compared to the standard (strong) equilibrium concept. On the other hand, when the n-player equilibria are closed-loop, the convergence to the MFG equilibrium is known only when the MFG equilibrium is unique and the associated "master equation" is solvable and sufficiently smooth. This paper adapts the compactness arguments to the closed-loop case, proving a convergence theorem that holds even when the MFG equilibrium is nonunique. Every limit point of n-player equilibria is shown to be the same kind of weak MFG equilibrium as in the open-loop case. Some partial results and examples are discussed for the converse question, regarding which of the weak MFG equilibria can arise as the limit of n-player (approximate) equilibria.
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页码:1693 / 1761
页数:69
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