Intractable problems in control theory
SIAM Journal on Control and Optimization
Real and complex analysis, 3rd ed.
Real and complex analysis, 3rd ed.
Distributed algorithms for the computation of noncooperative equilibria
Automatica (Journal of IFAC)
Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
Approximating networks and extended Ritz method for the solution of functional optimization problems
Journal of Optimization Theory and Applications
Error Estimates for Approximate Optimization by the Extended Ritz Method
SIAM Journal on Optimization
Variational Analysis in Sobolev and BV Spaces: Applications to PDEs and Optimization (Mps-Siam Series on Optimization 6)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Algorithmic Game Theory
Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley Series in Probability and Statistics)
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Approximate Minimization of the Regularized Expected Error over Kernel Models
Mathematics of Operations Research
Neural Networks and Computing: Learning Algorithms and Applications
Neural Networks and Computing: Learning Algorithms and Applications
Comparison of worst case errors in linear and neural network approximation
IEEE Transactions on Information Theory
Sequential greedy approximation for certain convex optimization problems
IEEE Transactions on Information Theory
Geometric Upper Bounds on Rates of Variable-Basis Approximation
IEEE Transactions on Information Theory
Universal approximation bounds for superpositions of a sigmoidal function
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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Existence, uniqueness, and approximations of smooth solutions to team optimization problems with stochastic information structure are investigated. Suboptimal strategies made up of linear combinations of basis functions containing adjustable parameters are considered. Estimates of their accuracies are derived by combining properties of the unknown optimal strategies with tools from nonlinear approximation theory. The estimates are obtained for basis functions corresponding to sinusoids with variable frequencies and phases, Gaussians with variable centers and widths, and sigmoidal ridge functions. The theoretical results are applied to a problem of optimal production in a multidivisional firm, for which numerical simulations are presented.