Neural Mean-Field Games: Extending Mean-Field Game Theory with Neural Stochastic Differential Equations

ArXi:2504.13228v4 Announce Type: replace Mean-field game theory relies on approximating games that are intractable to model due to a very large to infinite population of players. While these kinds of games can be solved analytically via the associated system of partial derivatives, this approach is not model-free, can lead to the loss of the existence or uniqueness of solutions, and may suffer from modelling bias. To reduce the dependency between the model and the game, we