Sequential Propagation of Chaos for Mean-Field BSDE Systems  

Sequential Propagation of Chaos for Mean-Field BSDE

作　　者：Xiaochen LI Kai DU 

机构地区：[1]Shanghai Center for Mathematical Sciences,Fudan University,Shanghai 200433,China. [2]Shanghai Artificial Intelligence Laboratory,701 Yunjin Road,Shanghai 200433,China

出　　处：《Chinese Annals of Mathematics,Series B》2024年第1期11-40,共30页数学年刊（B辑英文版）

基　　金：supported by the National Natural Science Foundation of China(No.12222103);the National Key R&D Program of China(No.2018YFA0703900).

摘　　要：A new class of backward particle systems with sequential interaction is proposed to approximate the mean-field backward stochastic differential equations.It is proven that the weighted empirical measure of this particle system converges to the law of the McKean-Vlasov system as the number of particles grows.Based on the Wasserstein met-ric,quantitative propagation of chaos results are obtained for both linear and quadratic growth conditions.Finally,numerical experiments are conducted to validate our theoretical results.

关 键 词：Backward propagation of chaos Particle system Sequential interaction McKean-Vlasov BSDE Convergence rate 

分 类 号：O211.63[理学—概率论与数理统计]