Recent developments in machine learning methods for stochastic control and games

Artificial neural networks and deep learning (68T07) Differential games and control (49N70) Optimal stochastic control (93E20) Stochastic learning and adaptive control (93E35) Mean field games and control (49N80)

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A fast iterative PDE-based algorithm for feedback controls of nonsmooth mean-field control problems
Error estimates for physics-informed neural networks approximating the Navier-Stokes equations
\textit{A posteriori} error estimates for fully coupled McKean-Vlasov forward-backward SDEs
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