Aug 12, 2024 · In this paper, we provide a flexible machine learning framework for the numerical solution of potential MFG and MFC models.

Aug 12, 2024 · Mean field games (MFG) and mean field control (MFC) are critical classes of multiagent models for the efficient analysis of massive populations of interacting ...

Aug 19, 2024 · In this paper, we mainly focus on the numerical solution of high-dimensional stochastic optimal control problem driven by fully-coupled forward-backward ...

Aug 8, 2024 · The RFM is in some sense the simplest possible machine learning model; it may be viewed as an ensemble average of randomly parametrized functions: an expansion ...

Aug 29, 2024 · For optimal control problems, the condition could correspond to the initial state, while the QoI embodies the control signal, with different control dynamics ...

Aug 12, 2024 · We develop a novel framework to learn the MFG solution operator. Our model takes a MFG instances as input and output their solutions with one forward pass.

2 days ago · Finally, the optimal control and value function are approximated by neural networks trained via adversarial learning using the derivative-free formulation. This ...

3 days ago · Abstract. This paper introduces an efficient tensor-vector product technique for the rapid and accurate approximation of integral operators within ...

Aug 21, 2024 · Mean field games (MFG) and mean field control problems (MFC) are frameworks to study Nash equilibria or social optima in games with a continuum of agents.

Aug 27, 2024 · Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State. Washim Uddin Mondal ...