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Approximation structures with moderate complexity in functional optimization and dynamic programming.

, , , , and . CDC, page 1902-1908. IEEE, (2012)

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Can we cope with the curse of dimensionality in optimal control by using neural approximators?, , and . CDC, page 3540-3545. IEEE, (2001)Neural approximations for feedback optimal control of freeway systems., , , and . IEEE Trans. Vehicular Technology, 50 (1): 302-313 (2001)Neural networks for feedback feedforward nonlinear control systems., and . IEEE Trans. Neural Networks, 5 (3): 436-449 (1994)A Combinatorial Method for Health-Care Districting., , and . Optimization Techniques, volume 40 of Lecture Notes in Computer Science, page 116-130. Springer, (1975)A receding-horizon estimator for discrete-time linear systems., , , , and . ECC, page 3753-3758. IEEE, (2001)Distributed-information neural control: the case of dynamic routing in traffic networks., , and . IEEE Trans. Neural Networks, 12 (3): 485-502 (2001)Neural approximation of team optimal dynamic routing in IP networks., , , , and . CDC, page 5140-5145. IEEE, (2004)Optimal control of communication in energy constrained sensor networks through team theory and Extended RItz Method., , , and . IJCNN, page 1372-1379. IEEE Computer Society, (2009)Radial basis functions and multilayer feedforward neural networks for optimal control of nonlinear stochastic systems., and . ICNN, page 1853-1858. IEEE, (1993)Feedback Optimal Control of Distributed Parameter Systems by Using Finite-Dimensional Approximation Schemes., , and . IEEE Trans. Neural Networks Learn. Syst., 23 (6): 984-996 (2012)