Discrete time McKean-Vlasov control problem: a dynamic programming approach
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Abstract (arXiv)
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean-Vlasov control problem.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Nov 2015.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 0; 2026: 2.
4 papers.
- 2021Reinforcement Learning for Mean Field Games, with Applications to Economicscited by 15
- 2026An Optimal Control Approach To Transformer Trainingcited by 3
- 2023MESOB: Balancing Equilibria & Social Optimalitycited by 1
- 2026Robust Q-learning for mean-field control under Wasserstein uncertainty in common noisecited by 0
- 2026Robust Q-learning for mean-field control under Wasserstein uncertainty in common noise18 Jun 2026
- 2026An Optimal Control Approach To Transformer Training10 Mar 2026
- 2023MESOB: Balancing Equilibria & Social Optimality16 Jul 2023
- 2021Reinforcement Learning for Mean Field Games, with Applications to Economics25 Jun 2021