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Learning in discrete-time average-cost mean-field games
(IEEE, 2021)
In this paper, we consider learning of discrete-time mean-field games under an average cost criterion. We propose a Q-iteration algorithm via Banach Fixed Point Theorem to compute the mean-field equilibrium when the model ...
Regularized stochastic team problems
(Elsevier, 2021-03)
In this paper, we introduce regularized stochastic team problems. Under mild assumptions, we prove that there exists a unique fixed point of the best response operator, where this unique fixed point is the optimal regularized ...
Large deviations principle for discrete-time mean-field games
(Springer, 2021-11)
In this paper, we establish a large deviations principle (LDP) for interacting particle systems that arise from state and action dynamics of discrete-time mean-field games under the equilibrium policy of the infinite-population ...
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