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Tackling mean-field control with common noise requires a novel integrated q-function (Iq-function) approach to identify optimal policies as fixed points.
Q-learning can now tackle mean-field control problems with common noise, even when the ideal data is unobservable, opening the door to more realistic and complex multi-agent control scenarios.
