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- W2924868653 abstract "This paper studies convex dynamic team problems with finite and infinite time horizons. First, we introduce two notions called exchangeable teams and symmetric information structures. We show that, in convex exchangeable team problems, an optimal policy exhibits a symmetry structure. We give a characterization for such symmetrically optimal teams for a general class of convex dynamic team problems. While for partially nested LQG team problems with finite time horizon it is known that the optimal policies are linear, for infinite horizon problems the linearity of optimal policies has not been established in full generality and typically not only linearity but also time-invariance and stability properties are imposed apriori in the literature. In this paper, average cost finite and infinite horizon dynamic team problems with a symmetric partially nested information structure are studied and globally optimal solutions are obtained where we establish linearity of optimal policies. In addition, for convex mean field teams with a symmetric information structure, through concentration of measure arguments, we show the convergence of optimal policies for mean field teams with $N$ decision makers to the corresponding optimal policies of mean field teams. Moreover, we discuss average cost infinite horizon state feedback problems for LQG dynamic teams with sparsity and delay constraints." @default.
- W2924868653 created "2019-04-01" @default.
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- W2924868653 date "2019-03-27" @default.
- W2924868653 modified "2023-09-27" @default.
- W2924868653 title "On Convex Stochastic Dynamic Teams with Infinite Horizons and Decision Makers" @default.
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