Proves first-order convergence of semi-discrete monotone schemes for HJ equations on Wasserstein space over finite graphs via a weighted L1 adjoint framework with boundary-vanishing weight and bootstrap estimates on discrete gradients.
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A convergent semi-Lagrangian scheme for non-local first-order mean field games is constructed, together with a learning value algorithm and policy-iteration acceleration, supported by convergence proofs and numerical experiments.
Proves existence and uniqueness of mean-field equilibrium in a stochastic optimal investment game with price interaction through expected production capacity, for finite and infinite time horizons, plus the deterministic counterpart.
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First-Order Convergence of Monotone Schemes for Hamilton--Jacobi Equations on the Wasserstein Space on Graphs
Proves first-order convergence of semi-discrete monotone schemes for HJ equations on Wasserstein space over finite graphs via a weighted L1 adjoint framework with boundary-vanishing weight and bootstrap estimates on discrete gradients.
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A semi-Lagrangian scheme for First-Order Mean Field Games based on monotone operators
A convergent semi-Lagrangian scheme for non-local first-order mean field games is constructed, together with a learning value algorithm and policy-iteration acceleration, supported by convergence proofs and numerical experiments.
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Existence and uniqueness results for a mean-field game of optimal investment
Proves existence and uniqueness of mean-field equilibrium in a stochastic optimal investment game with price interaction through expected production capacity, for finite and infinite time horizons, plus the deterministic counterpart.