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Eigenvalues and dynamical properties of weighted backward shifts on the space of real analytic functions
(Institute of Mathematics Polish Academy of Sciences, 2018)
Usually backward shift is neither chaotic nor hypercyclic. We will show that on the space A(Omega) of real analytic functions on a connected set Omega subset of R with 0 is an element of Omega, the backward shift operator ...
Frequently hypercyclic weighted backward shifts on spaces of real analytic functions
(TÜBİTAK, 2018)
We study frequent hypercyclicity in the case of weighted backward shift operators acting on locally convex spaces of real analytic functions. We obtain certain conditions on frequent hypercyclicity and linear chaoticity ...
Value iteration algorithm for mean-field games
(Elsevier, 2020-09)
In the literature, existence of mean-field equilibria has been established for discrete-time mean field games under both the discounted cost and the average cost optimality criteria. In this paper, we provide a value ...
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 ...
Q-learning in regularized mean-field games
(Springer, 2023-03)
In this paper, we introduce a regularized mean-field game and study learning of this game under an infinite-horizon discounted reward function. Regularization is introduced by adding a strongly concave regularization ...
Learning mean-field games with discounted and average costs
(Microtome Publishing, 2023)
We consider learning approximate Nash equilibria for discrete-time mean-field games with stochastic nonlinear state dynamics subject to both average and discounted costs. To this end, we introduce a mean-field equilibrium ...
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