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Exploratory LQG Mean Field Games with Entropy Regularization
We study a general class of entropy-regularized multi-variate LQG mean field
games (MFGs) in continuous time with distinct sub-population of agents. We
extend the notion of actions to action distributions (exploratory actions), and
explicitly derive the optimal action distributions for individual agents in the
limiting MFG. We demonstrate that the optimal set of action distributions
yields an -Nash equilibrium for the finite-population
entropy-regularized MFG. Furthermore, we compare the resulting solutions with
those of classical LQG MFGs and establish the equivalence of their existence.Comment: To appear in Automatic