Provides non-asymptotic error bounds O(h^{1/4}) + O(M^{-γ}) for Euler discretization and interacting particle approximations of path-dependent MKV control, plus a neural policy-gradient method.
Mean-field neural networks-based algorithms for McKean-Vlasov control problems
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Neural actor-critic method for high-dimensional HJB PDEs converges in Sobolev space to an infinite-dimensional ODE whose fixed points solve the stochastic control problem under a convexity-like Hamiltonian assumption, with numerical success up to 200 dimensions.
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Numerical Approximation for Path-Dependent McKean-Vlasov Control with Non-Asymptotic Error Estimates
Provides non-asymptotic error bounds O(h^{1/4}) + O(M^{-γ}) for Euler discretization and interacting particle approximations of path-dependent MKV control, plus a neural policy-gradient method.
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Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies
Neural actor-critic method for high-dimensional HJB PDEs converges in Sobolev space to an infinite-dimensional ODE whose fixed points solve the stochastic control problem under a convexity-like Hamiltonian assumption, with numerical success up to 200 dimensions.